Professional Development

The Four Most Common Data Science Interview Questions and How to Prepare for Them

Interviewing for a data science role can be a daunting task, especially for those new to the field. I have lost count of the number of data science interviews I have had over the years, but here are the four most common questions I have encountered and strategies for preparing for each. Prepping for these questions is a great opportunity to develop your story thesis, the most important part of any data science interview.

Most Common Data Science Questions:

1) Tell me about yourself.

2) Describe a data science job you have worked on.

3) What kind of experience do you have with messy data?

4) What programming languages and software have you used?

Question 1: Tell me about yourself.

This is probably hands down the most common interview question across all industries and fields, not just data science, so the fact that it is the most commonly asked questions in data science interviews may not seem that surprising. A good answer is crucial to establish a favorable first impression and to lay your main story or thesis of who you are that you will come back to throughout the interview.

In data science interviews, I emphasize my passion for using data science tools to help organizations solve complex problems that were previously vexing. If you are unsure what your thesis is, I designed this activity to help people decipher it. Here is an example of how I would describe myself:

“I fell in love with data science because I enjoy helping organizations solve complex problems. In my past roles, I have used my combined data science and social science skills to explore and build solutions for complicated problems for which the typical ways of doing things within the organization have not worked. I am energized by the intellectual stimulation of breaking down complex problems and using data science to develop potential innovative yet useful solutions. What kind of problems do you guys have that has led you to need to find a data scientist like me?”

Your self-description should tell the story of who you are in a way that demonstrates how you would be a natural fit for the role and helpful to the organization. As your interview thesis, if you laid it out well, then every other question you answer will simply involve fleshing out one (or a combination) of those three basic parts of your self-story: 1) Who you are, 2) How your identity makes you a natural fit for the role, and 3) How this would benefit the organization.

Here are four other important observations to note about how I told my story:

I emphasized who I was – an innovator developing unique solutions to complex problems – while showing my innovator identity naturally connects with data science and could be helpful for the organization. You might not consider yourself an “innovator” per se, but the trick is to figure out who you are based on what energizes and impassions you and then show how performing the data science role you are applying for is a natural fit for who you are.
I told the story with normal words, not technical jargon. I have found that many, if not most, of my interviews, especially the first-round interviews, are with employees without technical expertise, and since you often do not know the level of technical expertise of the interviewer, it is better to err on the non-technical side.
I kept my story positive, only mentioning what I like to do. Sometimes people instinctively try to illustrate what they want by describing things they do not like to do: e.g. “At previous last job, I learned I do not like doing Y, so I am seeking to do X instead” or “I am doing Y, and I hate it. I want out.” I would describe these aspects of my story later if the interviewer asks, but I would stick with the positive at first: only mentioning what I want to do.
I used strong, subjective, even emotional phrases like “fell in love with,” “passionate about,” and “energized by.” At first glance, these phrases might seem overly informal, but I have found they help interviewers remember me. Do not overdo it, but being more vivid and personable is generally helps rather than hurts your interview chances for data science positions.

Question 2: Describe a data science project you have worked on.

This is the second most common question I encountered, so make sure you come prepared with an exemplar project to showcase. They may ask you a lot of questions about your project, so I would recommend choosing a project where you did an amazing job on, really knocked it out of the park and that you are proud of. Unless there are disclosure issues, post your work on GitHub, a blog, LinkedIn, or somewhere else online, and include a link to it in your job application.

How to explain the project will vary considerably depending on your interviewer’s degree of expertise. I generally start with a non-technical, high level explanation and provide the technical details if the interviewer(s) prompts me to with follow-up questions. This gives the interviewers the freedom to choose the level of technical expertise they would like in their follow-up. A data scientist interviewer worth his or her salt will quickly steer the conversation into more technical aspects of your project that he or she wants to learn more about, but even then, starting non-technical demonstrates that you know how to effectively communicate your work to non-technical audiences as well.

When describing your project, you are effectively telling the story of the project, and most project stories have the following core components:

Who: You are probably the story’s protagonist (it is your interview after all, so naturally pick a project or part of a project where you were the primary driver), but there are likely multiple important side characters that you will need to setup, like who commissioned the project, who it was for, who the data was about, and so on.
What: The problem, need, or question your project sought to address generally forms the “conflict” of the project story, so be sure to explain what led to the problem, need, or question (in stories, called the inciting incident).
When and Where: The timeframe setting/context in which the project took place (e.g., the organization you were working with or a class you took for which the project was for). How long you had to complete the project can also be important to establish.
How: What did you to solve the problem. If you tried a lot of approaches before discovering what works, the how includes both your methodological story and your final solution (that is part of the rising and falling action for how you overcame the project). This is the meat of your story. You will want technical and non-technical descriptions of the how:
- Technical How: Generally, the core two parts of a technical description are the model you used (and any you tried if applicable) and how you determined the features/variables you selected. Another important part might be how you cleaned and/or gleaned the data.
- Non-technical How: I have found that non-technical audiences usually do not glean much from either the model I ended using or my feature selection procedure. Instead, I explain what type of functionality I ensured the model had to solve the problem I had just setup: for example, “I built a model that calculated the probability of X phenomena based on data sources A, B, and C, testing various types of models to determine which would do this best, and then discerned which variables among those datasets were the best to use.” For a non-technical audience, that is generally enough. The core component for them is what goes into the model (the data), what result the model produced from it, and how that informed the problem, need, or question driving the project.

Finally, in your how explanation, make sure you slip in whatever programming languages and software you used: Python, R, SQL, Azure, etc.

Why: This is your explanation of why you chose the approach(es) you did for your how. Now, just like with the how, you will need a technical and non-technical explanations of the why.

Make sure your non-technical explanation of why aligns with your non-technical how. I commonly see data scientists make the mistake of going over a non-technical individual’s head by trying to provide a technical why explanation for their non-technical how. In particular, I would not explain the metric or criteria you used to compare models or decide the feature selection procedure in my non-technical explanation, since these will likely lose a non-technical person. If my non-technical how description focused what data the model used and what it did with it, then my non-technical why focuses on why building a model to do that mattered and how it helped others and/or myself in the real world.

What happened: This is the result of the project. Did you succeed or fail (or somewhere in between)? Was it useful for whoever you built it for? Were you able to conduct any follow-up analysis after deployment? Maybe most importantly, what did you learn from the experience? In narrative terminology, this is the resolution. The more you can quantitatively measure any outcomes the better.

These are the basic components of a project story. Here is the most common project I use, and when reading through it, feel free to analyze how I present each component of the story. I wrote this blog for a general audience, so I provided my non-technical how and why.

Question 3: What kind of experience do you have with messy data?

Interviewers ask me this question surprisingly frequently. They usually preface the question by explaining that they at the organization have a lot of messy data that would require cleaning/processing for their future data scientist. This is a great opportunity to showcase your comfort with data science and data science issues.

I typically answering something like this:

“Yes, I have had to organize and clean messy data all the time. That’s par for the course in data science: the running joke among data scientists is that 90% of any data science project is data cleaning, and 10% actually doing anything with it. At least you guys are honest about the fact that your data is messy. When I worked as a consultant, for example, I talked with many organizations about potential data science projects, and if they said their data was clean and ready to go, chances are they were lying either to themselves or to me about how messy and haphazard their data really was. The fact that you are upfront about the messiness of your data tells me that you guys as an organization are realistically assessing where you are and what you need.”

This answer not only establishes that I have handled messy data before but also normalizes the problem in the field as resolvable by an expert (like myself) and compliments them for being up front. Answering this question confidently and positively has uniquely put me at the top of the list as the front runner candidate in some interviews. Giving a good answer to is is a perfect opportunity to endear yourself with your interviewer.

Question 4: What programming languages and/or software have you used?

Even though a technical interviewer might ask this as well, I have encountered this question most frequently among non-technical interviewers. In my experience, fellow data scientist interviewers have more insider ways of deciphering whether you do in fact know data science, but for non-technical interviewers, this question is their initial way to probe that. Sometimes, they will cling to a laundry list of software and/or languages to determine whether you are qualified.

Now, I believe that having experience using the exact combination of softwares that the data science team you would be joining uses is generally not that important a criterion for job success. For a good data scientist, learning another software system or programming language once you know dozens is not that difficult of a task. But their question is completely natural and reasonable coming from their side, so you will have to answer it.

If they open-endedly ask what softwares and languages you have use, list through the ones you have used, maybe starting with the ones you use the most often. I generally start by mentioning Python, since not only is it my favorite language for data science (see this article) but also conveys that I am familiar with programming in general.

More often, though, they might ask whether you have used X software before, often asking whether you have used each software on a list they have in front of them. I would never recommend lying by claiming that you have experience with a software you have never used, but I would recommend recasting a “No” by providing an equivalent software to it that you have worked with. Here is an example:

“No, I have not used Julia, but that is because I prefer using Python for what others might use Julia for. Python is an equivalent high-functioning programming language in complexity, and the data science teams I worked on happened to prefer it over Julia.”

This not only conveys the “No” in a bit more of a positive light, but it shows that you are familiar with the software he or she just mentioned and confident about using it to match your would-be team.

Question 5: What are you looking for in a job?

Most often, this is the last major question interviewers ask me, but I have gotten it at the beginning as well. They probably save it until the end, because the question transitions very easily to the next part of the interview: either them describing the role or you providing any questions you have.

If you did a good job laying out your thesis story in the first question, then here you simply restate it from a different angle. You already laid the groundwork, and you are just bringing it home at this point. If they ask me this at the beginning of the interview before the “Tell me about yourself” question, then I use this question to retell my thesis story from this new angle.

Here is my typical answer:

“Like I said, I am energized by figuring out how to help organizations solve complex data science problems. Over the years, I have found two concrete things in an organization help me with this. First, I thrive in stimulating work environments where I am given the space and resources to think creatively through problems. Second, I also need to be able to work with people from a variety of backgrounds and disciplines from whom I can learn from and develop innovative approaches to the problem at hand. You guys seem to provide both. [I then conclude by explaining why they seem to provide both based on what you learned about the organization during the interview, or if we have not had a chance to talk about them yet, ask about these within the organization.]”

Notice that the first sentence references my self-explanation answer to the “Tell me about myself” question. If they ask this question before I have given that spiel, I spend about 30 seconds or a minute providing a condensed self-introduction and then continue with the rest of the answer.

Conclusion

These are the five most common data science interview questions I have encountered and how to prepare for them. I have found that when data scientists give advice on how to prepare for job interviews, they often focus on preparing for highly technical, factual questions (e.g., here and here). Even though having a solid data science foundation can be important, refining your overall story thesis – who you are, what you are passionate about doing, and how that relates to this job – is far more important to advance through the interview process.

I have found that humans, even supposedly “nerdy” data scientists, tend to connect with people and stories, so if you can hook them there, they generally remember you better and are more likely to hire you. When you have a compelling story, every other question will naturally fall into place as an intuitive further clarification of that overall story.

Photo Credit #1: Work With Island at https://unsplash.com/photos/FX2QA0TMEYg

Photo Credit #2: Free-Photos at https://pixabay.com/photos/glasses-reading-glasses-spectacles-1246611/

Photo Credit #3: geralt at https://pixabay.com/illustrations/questions-font-who-what-how-why-2245264/

Photo Credit #4: Darwin Vegher at https://unsplash.com/photos/W_ZYCEUapF0

Photo Credit #5: geralt at https://pixabay.com/illustrations/software-program-cd-dvd-disc-pack-417880/

Photo Credit #6: jenoliver777 at https://pixabay.com/photos/horses-dogs-groundwork-blaze-2888749/

The Job Hunt (Part 1): Introduction

For the last few months, I have been considering a mini-blog series on the job hunt, and (at the time I am writing this) the economic downturn resulting from the coronavirus pandemic has made a discussion on finding a job even more relevant.

In this mini-blog series, I will focus on the following topic areas in the job hunt:

Job Hunt Preparations: Self-care, goal setting, daily habits, vocational reflection, etc.
Learning about potential opportunities: networking, job searching, etc.
Marketing yourself for employers: writing a resume/CV and cover letter, building a portfolio, etc.
Developing your own skill sets: Navigating whether to develop your skills and which resources to use

This blog may be useful to you if you are in the following situations:

Recently left or about to leave a job (for whatever reason) and are looking for another
Have been disconcerted at your current job (again for whatever reason) and have decided to look elsewhere
Recently graduating from school or some other kind of training and seeking to enter the workforce
Finding gigs is a regular part of your work

(Final Note: Even though my blog focuses on the integration of data science and anthropology, in this mini-series, I intend my advice for just about any industry. Data science and anthropology are where I have most experience in, though, so, of course, I might implicitly have a bias towards strategies what works in those fields.)

Photo/Graph credit: MIH83 at https://pixabay.com/illustrations/job-application-job-search-1344744/

The Job Hunt (Part 2): Preparing Yourself

This is my first blog on the Job Hunt mini-series. When starting to embark on finding a new job, preparing yourself is the most important first step, so the first set of posts will focus on the initial work necessary to launch yourself going forward.

Prepare yourself both physically, including financially and logistically, but more importantly mentally and emotionally for what you are about to undertake. The job hunt is often an adventure, so readying yourself is crucial.

Here are three basic ways to prepare yourself:

Give yourself time to process what you’re leaving/left.

Take stock mentally, emotionally, and materially for the long haul.

Be patient and know what you can control.

Give yourself time to process what you’re leaving/left.

Frequently when people are looking for a job, they recently ended or would like to end some prior situation: maybe something happened causing them to resign or be let go, or they are stressed for whatever reason at their current position and thus seeking something else. In such situations, make sure you explicitly take time to process and heal from whatever you may be coming out of.

How to do so might depend on both who you are and what you have encountered. Maybe you need to replenish yourself from burnout, emotionally and/or mentally process what happened, or reassess who you are. This will take time, and that it does is in no way a negative reflection of you.

Balance, Meditation, Meditate, Silent, Rest, Sky, Sun

Be conscientious about developing meaningful practices that will rejuvenate you and help you process what happened. Journal, take up a hobby, talk with friends or family, or do whatever helps you. After a day of exertion, our bodies physically need to sleep at night to rebuild the muscle tissue for a new day of adventures. Our emotional and mental faculties often work similarly: taking the time to slow down and process what happened will allow you to move forward in pursuit of your next occupational adventure.

Take stock for the long haul.

Be prepared mentally, emotionally, and materially for the long haul. I frequently hear people say that it takes on average six months to find a job. At the time of writing this, the economy is bad, and it could be longer. Materially and financially take stock of how many resources you have and how you can plan to get by for a while.

Prepare yourself mentally and emotionally a long trek in finding the next job. Try to resist the urge to appease yourself with the potentially false promise of a quick turnaround and ignore any swindlers trying to sell you the same.

Telling yourself that it could take months of grueling work to find a job will help you in the long run. It’ll be much easier on you to have a shorter-than-expected job hunt than to have your high hopes for a quick out crushed.

The job search is (almost always) a long and arduous process. Be ready for that.

To me personally, the job hunt feels like a tunnel: you hope/sense that there is a light at the end of it when you will find the next gig, but you do not know when it will come. It could always be tomorrow that you get that amazing job offer or several months from now.

This image has an empty alt attribute; its file name is Job-Hunt-Part-2-Picture-2-1-1024x682.jpg

There is generally light at the end of the tunnel, but that doesn’t mean the experience isn’t difficult. Having unrealistic expectations will only make the dark times ahead feel all the darker.

Be patient and know what you can control.

The ancient stoic philosophers emphasized not holding yourself accountable to what is beyond your control, and I have found that the job hunt can necessitate its own version of stoicism. You can do a lot to better your application, find the right job, connect with the right people, and these are important.

But, there is always so much about it that you cannot control. You cannot fully control where employers on the other side are coming from and what decisions they make: how and where they look for candidates, what they think of you and whether they value you, or even whether organizations/companies have an open position in the first place.

One pro of the online applications is that we even more equipped to apply to positions around the world, but one con is that thousands of applications go unread. Job prospects can often come and go based on wider structural societally factors – like a failing economy – or the successes or failures of that specific organization. You can do everything right in application and still fail for reasons outside of your control.

This image has an empty alt attribute; its file name is Job-Hunt-Part-2-Picture-3.jpg

You can and should strive to make your application as strong as possible: both presenting yourself in the best possible light and searching within your means for the best job openings for you. But, as in Richard Niebuhr’s famous prayer, possessing the wisdom to know what you can and cannot change is crucial. This requires that you be patient with yourself if and when you fail so that you can continue to pick yourself back up and try again.

Photo/Graph credit #1: Engin Akyurt at https://www.pexels.com/photo/woman-holding-black-flag-1571734/

Photo/Graph credit #2: realworkhard at https://pixabay.com/photos/balance-meditation-meditate-silent-110850/

Photo/Graph credit #3: Free Photos at https://pixabay.com/photos/person-man-male-worker-inside-731151/

Photo/Graph credit #4: Flazingo Phots at https://www.flickr.com/photos/124247024@N07/14110060693/

The Job Hunt (Part 3): Pace Yourself and Set Goals

Pacing yourself is crucial for finding a job, and setting appropriate goals is the best way to ensure that you have a workable pace.

The job hunt is more like a marathon than a sprint, but at the beginning many encounter a strong temptation to jump in headfirst with a full sprint. Like the Hare in Aesop’s Fable, they rush into the process, expecting a quick turnaround in a few days or weeks, if only they can complete everything they have to.

Sometimes this works and they do find a job, and if so, more power to you. But, frequently this simply exhausts the person after the initial transition sets in. You cannot sprint your way through a marathon but must learn to pace yourself, lest you deplete critical energy during your initial charge.

On the other extreme, the job hunt seems uniquely set up to enable procrastination. Fixing your resume, reaching out to someone, filling out that online job application, etc. are important but frequently have undefined deadlines, meaning that you can always put it off until tomorrow. This fact coupled with the emotional energy needed to put oneself out there means that many procrastinate on key activities. This can include the exhausted sprinters who, after the initial high of their sprint crashes, often settle into an equally ineffective procrastination.

Making and keeping effective goals is the answer to both pitfalls. For sprinters, well-paced goals channel your initial energy into something productive while pacing yourself in the long run, and for procrastinators, daily and weekly goals keep you productive now at chipping away the necessary long-term complex tasks.

What I Do

So then, how do you set proper goals for the job search? Here is a breakdown of how I typically set goals:

I break down what I need to do into a series of tasks: networking/connecting with people, submitting job applications online, working on my resumes and cover letters, etc. (I will discuss the importance of and break down how to do each these in more detail in later articles.)

For quantifiably measurable tasks, like connecting with people and applying to jobs, I set a reasonable weekly goal like the following:

Reach out to 20 people a week, a.k.a. 4 people a day during the week (taking the weekends off)

Apply to 12 jobs a week, a.k.a. 3 a day during the week

Now, I prioritize reaching out to people over submitting online applications, because I have found networking to lead to more jobs interviews than submitting online applications, something I will discuss in more detail in a future article.

For qualitatively measurable tasks, like perfecting my resumes and cover letters, I generally set a certain amount of time per day/week to work on until that task is complete. For example, I might work on my resume for 25 minutes a day, for example, until the version I have for each type of job is of the quality I desire. This allows me to slowly chip away at the task.

The point of these goals is to give me the daily and weekly impetus I need to work through a much more complicated task. In the job search, there will be many necessary activities that I can always put off until tomorrow, which means that if I am not careful, I will put them off indefinitely.

By setting goals, I break down each complex task into smaller, manageable and tangible parts that I can slowly chip away at every day. Editing for 25 minutes or reaching out to 4 people is not that difficult, overwhelming, or time-consuming to complete right now, so every day I can easily manage it. The effects of these smaller parts are small at first, but over the course of a few weeks, they snowball into tackling the wider task/goal.

Goal Setting Yourself

So, how do you set reasonable goals, then? Well, the details of the goals you make are up to you and what you can handle given your schedule.

First, however, I would recommend you list out all the tasks you need to complete in order to find a job. For me, in the example above, that was networking, submitting online applications, and writing resumes and cover letters. What do you need to do?

Searching for jobs and bettering one’s application (which these three activities are examples of) are two common types of activities that job seekers must perform, so they are a good place to start. Later articles in this series will discuss several potential activities to consider in later articles as well.

After mapping out what you need to do, I would recommend the following criteria for thinking through the process:

1. Sufficiency: Give yourself enough time to work on the given task each day to slowly chip away at it overtime.
(For example, reaching out to 1 person a day would not enable me to complete my overall networking task quick enough, but 4 people a day could.)

2. Completable: At the same time, make sure your daily goal is completable each day.
(For example, reaching out to 20 people a day would be too high for me, given my schedule, but 4 people a day I have found perfectly doable even on hard days)

3. Resting and Reevaluating: Officially include time to rest from your goals and reevaluate what is working and not working about them.
(Notice I finished all my weekly goals during the week and did not work during the weekend. This both allowed me time to rest and recuperate from the job hunt and gave me space to disengage for a few days to reassess my goal setting. One should remove oneself from one’s goal setting rhythm periodically, because such space allows you to reassess whether that rhythm is working. It is smart to graft such breaks officially into your goals, and for many people, weekends for a natural time to do that. Do it when it makes the most sense for you, though.)

Sufficiency: Give yourself enough time to work on the given task each day to slowly chip away at it overtime.

(For example, reaching out to 1 person a day would not enable me to complete my overall networking task quick enough, but 4 people a day could.)

2. Completable: At the same time, make sure your daily goal is completable each day.

(For example, reaching out to 20 people a day would be too high for me, given my schedule, but 4 people a day I have found perfectly doable even on hard days.)

3. Resting and Reevaluating: Officially include time to rest from your goals and reevaluate what is working and not working about them.

(Notice I finished all my weekly goals during the week and did not work during the weekend. This both allowed me time to rest and recuperate from the job hunt and gave me space to disengage for a few days to reassess my goal setting. One should remove oneself from one’s goal setting rhythm periodically, because such space allows you to reassess whether that rhythm is working. It is smart to graft such breaks officially into your goals, and for many people, weekends for a natural time to do that. Do it when it makes the most sense for you, though.)

Conclusion

The job hunt is often a marathon, taking several months, so setting sufficient yet completable goals with adequate rest is the most important single activity you can do to pace yourself.

Goal setting prevents you both from starting out sprinting way faster than you should and thus just tiring yourself out in the long run, and from procrastinating on going forward at all.

Finding a job is doable but prepare yourself. It can be a long journey, so you need to treat it as such.

Photo Credit #1: Shannon McGee at https://www.flickr.com/photos/shan213/5860844312/

Photo Credit #2: OpenClipart-Vectorsat https://pixabay.com/vectors/checklist-task-to-do-list-plan-1295319/

Photo Credit #3: gerart at https://pixabay.com/photos/students-board-drawing-learn-start-4190327/

Photo Credit #4: Markus Winkler at https://unsplash.com/photos/LNzuOK1GxRU

The Job Hunt (Part 4): Self-Reflection Activity

What are you looking for in a new job? Looking for jobs provides a unique opportunity to either refine what one has been doing or to explore something new. Many people I have talked with who are searching for a job struggle with determining what they want: ranging from new graduates just entering (or reentering) the job market to people discontented with their current work. In addition, I have seen even more people, even those completely confident in what they do but for whatever reason lost their current position, struggle to articulate what they are looking for to potential employers.

This is a self-reflection activity to address both of those: think through what you want to do and articulate it concisely and passionately to others. It helps form your vocation, not only guiding what kind of positions you look for but also illuminating your overarching story you will tell others during interviews.

Step 1	List out five activities that you have done in the last few years that inspire you.
Step 2	List out five activities that you have done in the last few years that have drained/frustrated you.
Step 3	For each activity on both lists, then write out what about it inspired you and what about it drained you.
Step 4	Look through both sets of lists for common features.
Step 5	Synthesize these common features into a one- to two-sentence story.
Step 6	Tell this story to others who are close to you and practice it when appropriate with others.

Here is how it works:

Step 1: List out five activities that you have done in the last few years that inspire you.

People, Girls, Women, Students, Friends, Talking

An activity can be just about anything you have done: a job, a course you have taken, a specific project you have worked on, a hobby or pastime, volunteer activity, something you have done with family or around your home, and so on.

By “inspire,” I mean that the activity gave you energy, galvanized you, motivated you, gave you passion or inspiration, or otherwise gave your life and fulfillment doing it. This likely meant that you enjoyed the activity, but it is something deeper: that the activity gave you positive meaning/purpose, energy, motivation, or fulfillment, more than simply being fun. You felt alive while doing it.

These activities may overlap: for example, you may mention both an overall job you held that inspired you and a specific project you worked on in that job that was especially fulfilling, or both an inspirational course you took and a particular project in that course that was particularly motivating. Just about anything you have done could be an activity.

Step 2: List out five activities that you have done in the last few years that have drained/frustrated you.

Like with the five energizing activities, these may be just about anything and may even overlap with the previous list (e.g. a job might energy you overall but a part or aspect of it might have drained you). By “drained/frustrated you,” I mean the exact opposite: instead of energizing or galvanizing you, it sucked the life out of you, maybe leaving you feeling depleted, frustrated, or empty.

Note, however: Draining and frustrating you is not the same as simply tiring you. We often feel tired after doing any intense activity, whether we enjoy that activity or hate it. For example, I love playing basketball, but after playing for several hours, I will feel tired, even though I still felt stimulated while playing. Often being tired is simply the result of a full day’s work, and often many activities that fulfill or motivate us make us especially tired as well because we do them enthusiastically. An activity that drains or frustrates you takes motivation or passion from you while doing it: maybe feeling like it is sucking something out of you to complete.

Step 3: For each activity on both lists, then write out what about it inspired you and what about it drained you.

Young, Woman, Girl, Lady, Female, Work, Working, Study

Yes, I mean write out both what inspired and drained you for the items on both lists. For the inspired activities, likely listing what about it inspired you will be easier than listing what about it drained you. But, even the most amazing activities have something about them that drained you. Thinking about both the good and the bad of each activity is crucial to self-reflect on what you want to do. Since these activities have been inspired for you, the pros will likely outweigh the cons, yet some cons must almost certainly exist.

Likewise, for the activities that drained you, list out both what inspired and drained you even if the latter outweighs the former.

I typically treat this like a brainstorm session writing out whatever comes to mind. For each activity, I make a column for inspired and another for draining and list out as many aspects I can think of for each as they come to mind.

Step 4: Look through both sets of lists for common features.

Take some time away from the list, maybe a day or so if you can. When you are ready, reread it, analyzing for common themes. Are there any common patterns to what inspired you between the activities? Are there any patterns in what drained or frustrated you?

After initially looking through it yourself, feel free to show the list to someone or a couple people who know you well: like a spouse, other family member, or close friend. Ask him or her what patterns he or she notices and what he or she thinks of your patterns.

Before giving your thoughts, I would recommend first asking your confidant what patterns he or she notices, simply listening and taking notes, without commenting much. Then only after he or she is finished share the ones you found and ask his or her take on those. That way you can hear your confidant’s initial thoughts unhindered before you influence his or her perspective by telling your own.

Write all these patterns out: both what you noticed and what anyone else you showed it to noticed. Then see whether there are any common features between you guys. Feel free to list those out as well.

Step 5: Synthesize these common features into a one- to two-sentence story.

Chalkboard, Story, Blogging, Believe, Blackboard, Chalk

Your next step is to organize these different features into a story: determining what the various items on both lists have in common and synthesizing these into a cohesive whole.

Here are a few potential questions to ask:

Are there any similarities between what energized you, like similar types of activities that gave you energy? For example, maybe many of the activities that inspired you involve working and communicating with others, or solving a complex problem, or developing or organizing something, or logical or analytical work, a technical skill, and so on.
Likewise, are there any similarities among the activities that drained you? Maybe one of the types of activities I gave in the first question frequently drained you?
Are there any connections between the activities that energized and drained you? This is often the case. For example, for me, coming up with innovative ways to solve complex problems energizes me, but following repetitive procedures often drain me (see my next article, where I will do this activity myself as an example, for more detail). These are flip sides of the same coin: Developing innovative and unique strategies energized me, and its opposite, following rote procedures, drain me. Likewise, see whether any of the inspiring and draining themes mirror each other.

Now synthesize these themes into a cohesive one- or two-sentence story about who you are and what you like to do. Think of this as like a thesis statement for an essay, summarizing the main points of who you are in a way that you can go into more detail on if someone’s interested.

My explanations might use the following types of sentence structures. Feel free to use these as inspirations to get a sense for how to structure your ideas succinctly, but if you have other ways of phrasing it, that is fine as well:

“I have a passion for _, but I get frustrated when _.”
“_ gives me energy.”
“_ makes me feel stifled.”
“I tend to appreciate roles that involve _, _, and_.”
“I should avoid roles that involve _, _, and _.”

two women sitting beside table and talking

To do this, I typically employ the following strategy:

First, I talk it out with a friend or family member (likely the same person or people I shared my notes with for Step 4) or, if need be, by myself. I start by simply explaining all the items on the list one by one.

Second, without looking at my notes, I describe myself completely from memory to my friend/family member. I pretend that I am introducing myself in an interview, starting with something like, “Hello, my name is Stephen. I am passionate about…” Then I analyze what I changed when I spoke off script: What made the cut; how did I phrase things in the moment, what seemed the most important to talk about, and so on?

Typically, the first time I introduce myself, it never comes out right. Maybe I begin a certain sentence but realize mid-stream that I need to start over and phrase it differently. If that happens to you, that is fine. The first time you do this often feels awkward, but working through the kinks of your spiel out now in front of a trusted confidant or by yourself is much better than stumbling through your words in a job interview for a role you really want.

I then go through that self-summary a few more times until I have a better sense for what to say. If I began one way but had to correct myself, or if I stuttered through a part, I repeat it again and again until I phrase it the way I want, and I am confident in my delivery.

Once I have my spiel, I then cut it in half. When I have done this exercise with others, I often notice people’s spiels are around two-three minutes and about twelve or so sentences. Awesome, there is a time for such long descriptions – like that infamous first question in an interview, “Tell me about yourself.” But, for now cut it in half. If you used twelve sentences, now use six or if you took three minutes, now say it in a minute and a half. Practice that a few times until you feel confident.

Then, once you get used to that shorter length, cut it in half again. Repeat this until your explanation is one- to two-sentences and/or no more than thirty-second long. That is your synthesis summary. Make sure you write it down and feel free to practice it until you can give it in your sleep. This will form the backbone of how you describe and sell yourself to employers.

Finally, think through what types of roles would match this: inspiring you while avoiding to the greatest extent possible what frustrates you. Some energizing passions lend themselves to certain positions and industries (or to avoiding others), but in my experience at least, many positions could match someone’s passions in multiple industries or fields.

Instead, it primarily tells you what you what to look for in the organizations and positions you consider. For example, if you are a data scientist, this tells you what type of data science job might work for you (or if you are considering leaving the field, what types of positions in any new field you might consider entering).

Your synthesis provides the criteria of what to look for in whatever industry or field you are considering. Thus, this will be what you communicate to others when talking with them about potential jobs.

Step 6: Tell this story to others who are close to you and practice it when appropriate with others.

People, Adult, Woman, Male, Coaching, Communicate

This summary forms the backbone of the story you tell others. When you network or go into a job interview, you will use this to describe yourself to others, so make sure you practice it until you can give reflexively. You can practice it by yourself, but I at least generally prefer practicing in front of others: friends, family, or the first people you network with so that I can see how other people respond and adjust what I say accordingly.

Feel free to develop a few different degrees of explanation in case you need them: a 10-second description, 30-second description, 1- to 2-minute description, and even a 3- to 5-minute much more detailed monologue. You will use different ones depending on the social situation and their degree of interest. In a future article, I will discuss how to describe yourself compellingly in more detail.

For now, pat yourself on the back: You did a lot. This self-reflection is crucial for determining what kind of role you want going forward and providing the narrative skeleton of how you present yourself to others. Such intense self-reflection can be taxing work, but it is ultimately worthwhile.

Photo Credit #1: Pexels at https://pixabay.com/photos/fountain-pen-note-notebook-page-1851096/

Photo Credit #2: StockSnap at https://pixabay.com/photos/people-girls-women-students-2557396/

Photo Credit #3: Allan Rotgers at https://www.flickr.com/photos/122662432@N04/13740073235/in/photostream/

Photo Credit #4: kaboompics at https://pixabay.com/photos/young-woman-girl-lady-female-work-791849/

Photo Credit #5: Kelly Sikkema at https://unsplash.com/photos/-1_RZL8BGBM

Photo Credit #6: 742680 at https://pixabay.com/photos/chalkboard-story-blogging-believe-620316/

Photo Credit #7: Christina at https://unsplash.com/photos/LQ1t-8Ms5PY

Photo Credit #8: Verteller at https://pixabay.com/photos/people-adult-woman-male-coaching-3275289/

The Job Hunt (Part 5): My Own Self-Reflection

In this article, I complete the occupational self-reflection I described in Part 4 as an example of what such a reflection might look like. Your story won’t be mine, so feel free to craft the reflection to fit your needs. This is just one sample of what it could look like.

Activity Overview:

Step 1	List out five activities that you have done in the last few years that inspire you.
Step 2	List out five activities that you have done in the last few years that have drained/frustrated you.
Step 3	For each activity on both lists, then write out what about it inspired you and what about it drained you.
Step 4	Look through both sets of lists for common features.
Step 5	Synthesize these common features into a one- to two-sentence story.
Step 6	Tell this story to others who are close to you and practice it when appropriate with others.

Step 1: List out five activities that inspire you.

Show Rate Predictor at BronxCare
Master’s Practicum
Ethno-Data Blog
Writing a Sitcom
Networking

Descriptions:

(Note: You wouldn’t likely need to explain what each activity is to yourself, since, well, you are the person who did them. Just listing them is fine. But I am describing my activities to help give you, reader, context since otherwise, you won’t likely know what I did.)

Show Rate Predictor at BronxCare: This was a major project I worked on at BronxCare. I worked with a clinic to build a machine learning show rate predictor that both calculated the probability an upcoming appointment would occur and estimated the number of appointments to expect for every doctors’ shifts. I started by conducting ethnographic user research into the problem to figure out exactly what they need, built two machine learning algorithms to provide the most useful information, and worked with a team to develop the app to communicate that findings to schedulers in real-time as they schedule.
Master’s Practicum: The University of Memphis’s Anthropology Department required a practicum project, a 300-hour or more project with an organization for the master’s degree and documenting a detailed research report on the work. I did my practicum with Indicia Consulting in the summer of 2018. Here is my full report for your reference.
Ethno-Data Blog: I am referring to this blog you are reading. So, if you are reading this, you have found it and know what it is.
Writing a Sitcom: I have been writing an animated sitcom, which a few of my artistic friends and I are planning on developing.
Networking: By this, I am thinking of the general activity of networking with other people to learn about their work and find connections with them. I do this particularly vigorously whenever I am looking for a job.

Now, yes, these are a range of projects: including a work project, a personal project, a school project, and finally a nebulous, informal activity like networking. This is by design, since encompassing a wide variety of different types of activities allows me to think about different facets of my life. Feel free to choose among any type of activities that would be most helpful for you.

Step 2: List out five activities that you have done in the last few years that have drained/frustrated you.

Comprehensive Exams
UX Research Consulting Project for Thriving Cities Group
Data Pulling at BronxCare
Retention Research Project with ServiceMaster
Secondary Math Teaching

More detailed explanations for your reference:

Comprehensive Exams: The University of Anthropology required a written comprehensive exam to graduate with a master’s degree. One must write a four in-class essays over the series of two days and then defend your answers to your committee.
UX Research Consulting Project for Thriving Cities Group: Thriving Cities Group was seeking to build an app to help non-profits coordinate with potential funders and chose Memphis, Tennessee as the starting place to launch their beta-version. They hired me as a UX researcher in preparation for this launch. I really enjoyed the UX research I did, but I also learned a lot about what I need when conducting research as a consultant with organizations.
Data Pulling at BronxCare: As a data scientist who specialized in developing machine learning and statistical models for data, my role as a data scientist at BronxCare typically did not require simple data queries to pull data for a project. But, occasionally it would. These would generally be one-time SQL queries into the database system (since another team would generally conduct repeating queries). This was my least favorite aspect of my job there.
Retention Research Project with ServiceMaster: As a data scientist, I worked on a year-long project building a model to predict and understand retention. I appreciated the idea of the project and the nature of the work, but its implementations had some issues: the abrupt departure of my manager who had commissioned the project, the lack of managerial buy-in for the project above him, issues collecting the necessary data, and departmental politics. These led to the project being overall frustrating, although also a learning experience on aspects of organizational research projects frustrate me.
Secondary Math Teaching: I taught secondary math in both Gary, IN and Chicago, IL for a few years before deciding to move into data science. Through this, I learned middle school and high school teaching is not a good fit for me.

Notice again that this list covers a variety of different types of projects from different contexts and times in my life. Feel free to do the same.

Step 3: For each activity on both lists, then write out what about it inspired you and what about it drained you.

Here are what aspects of each list energized me and frustrated me.

Note: Yes, I wrote both what energized me and what frustrated me for both lists. Even the most life-giving activities have aspects about them that frustrates you and the most frustrating activities have positive aspects. You learn a lot about thinking about the ugly in the good and the good in the ugly.

Energizing Activities

Energizing Activities	What Energized Me	What Frustrated
Show Rate Predictor at BronxCare	Trying to break down and solve a complex problem Figuring out the optimal machine learning models to useDesigning the software’s architecture and design Presenting/selling it to those in the clinic and receiving their buy-in/support	Bureaucratic red tape to get the proper software access to build the app Internal politics within the organization in getting the project off the ground
Master’s Practicum	The work itself: solving the problem and completing the task with Indicia Researching and seeking to rethink the historic relationship between anthropology and data science (my key intervention in my report) Presenting my work at conferences and the recognition through the various awards I received for innovative research	Committee members seemingly unwilling to entertain the thought of rethinking the discipline and its relationship to data science Committee members trying to cast my work as not anthropology because it did not fit their pre-assigned mold of what anthropology is
Ethno-Data Blog	Researching and developing interesting ideas, analysis, content, and explanations Writing blog postsEspecially writing this Job Hunt mini-series People coming to me saying they appreciated my blog and/or to ask questions about it	Using the WordPress software interface, particularly difficult is transferring articles from Word Documents in which I originally write to WordPress Rushing to meet posting deadlines
Writing a Sitcom	Developing the characters and their back stories Developing the overarching story structure for the show, outlining plots of specific episodes, and developing specific scenes Meeting with other artists to build a teamFeeling accomplished after finishing a draftSeeing other people excited about the idea	Editing: constantly polishing over the dialogue to make it shine (necessary but can be agonizing) Trelby’s interface (the screenwriting software I use)
Networking	Reaching out to and connecting with people Learning about other people and their work/experiences Thinking through ways to work together to solve problems	Its cyclic nature: constantly repeating the same cycle of reaching out to new people after concluding with current connection Monotony of reaching out: generally having the repeat the same set of tasks with minor yet hard to automate tweaks

Frustrating Activities

Frustrating Activities	What Energized Me	What Frustrated
Comprehensive Exams	Researching and developing the ideas to write about Writing out my prepared essays Wanting to talk about my intellectual journey and what anthropologists should learn from other disciplines and ways of thinking in order to think through how to engage with others in the world	Some of my committee members tried to force how I would think about things in the prompt by including what seemed like false premises into the questions themselves Some of committee members seemed to want me to parrot why anthropology is great and superior to all other disciplines Already dealing with burnout at the start of the assignment
UX Research Consulting Project for Thriving Cities Group	Hearing about people’s work at various non-profits around Memphis and their stories Analyzing issues with the app Working with engineers to come up with innovative solutions to the problems users brought up	The team seemed to be trying to find a problem that matched their “solution” they have already built instead of seeking to understand what issues/needs people have and then crafting a solution to those needs Top-down and forward-moving marching orders, which, in this instance, ignored the app’s severe issues with users on the ground
Data Pulling at BronxCare	Figuring out how to make Python scripts to automate these processes Building and analyzing models on the data after getting it together	Tedious Unnecessarily time-consuming yet trivial and unstimulating intellectually Data was stored in inconsistent and frustrating ways to access later
Retention Research Project with ServiceMaster	Planning and scoping out how to do the project The ethnographic portion of the project where interviewed and observed customer service representatives to learn about their experiences/expertise in communicating with customers Networking and collaborating with people from other teams to obtain data needed for the project and to learn about their own related projects Felt like the work connected well with the goals and bottom-line of both organization as a whole and my team specifically	When developing the research questions for the project, I felt like my supervisor could only think of limited, close-ended questions, instead of thinking open-endedly about the project. This seemed necessary given the complexity of the issue at hand. The research questions I was given for the project overly reductionist and simplisticThe data was half-hazard and messy, which made analysis with it difficult. Frustrating inter-departmental politics to access and use of the data I got
Secondary Math Teaching	Public speaking One-on-one teaching and mentoring Helping students develop the critical thinking skills to solve complex problems themselves	Managing childish/immature student behavior The tedium of grading Teachers did not have enough time to collaborate in the school.

Step 4: Look through both sets of lists for common features.

Looking through them, I found the following common features within both columns:

What Energized Me

What Frustrated

Talking with people and learning about what they are doing, whether through interviews, ethnographic research, or another means.

Networking and collaborating with others on a project

Analyzing and developing strategies to solve complex problems (e.g. whether the problem is data science-problem, mathematical/statistical, social or “people” problem, and so on.)

Communicating solutions to others (both conversationally and through public speaking) Writing creatively

Monotony, tedium, and rote work

Having to follow a seemingly unproductive and non-innovative procedure

Not having an innovative strategy I have been developing be understood or appreciated by those I am working with, especially my supervisor
Feeling my innovative ideas were shut down or attempted be shut down due to close-mindedness and the inability to think outside of the “conventional” ways of doing things

Step 5: Synthesize these common features into a one- to two-sentence story.

I did this synthesis twice, first writing a very large and cumbersome one-sentence version and then shortening it to make it more manageable.

Synthesis #1 – Large Cumbersome One-Sentence Version:

I am passionate about developing innovative ways to solve complex problems with others in situations for which the conventional approaches do not work, but I become frustrated when those with whom I am working (especially supervisors) do not understand or appreciate that innovation and try to enforce conventional ways of thinking that they have always employed.

Synthesis #2 – Final, Shortened Version:

My passion in a job is to develop innovative ways to solve complex problems, but I become frustrated when those with do not understand/appreciate that innovation and try to enforce conventional approaches.

Step 6: Tell this story to others who are close to you and practice it when appropriate with others.

I cannot easily show this stage in a written article like this, but suffice to say that it is extremely important to show and practice this in front of trusted family and friends. You learn a lot from their feedback.

Photo Credit #1: Pexels at https://pixabay.com/photos/fountain-pen-note-notebook-page-1851096/

Photo Credit #2: StockSnap at https://pixabay.com/photos/people-girls-women-students-2557396/

Photo Credit #3: Allan Rotgers at https://www.flickr.com/photos/122662432@N04/13740073235/in/photostream/

Photo Credit #4: kaboompics at https://pixabay.com/photos/young-woman-girl-lady-female-work-791849/

Photo Credit #5: Kelly Sikkema at https://unsplash.com/photos/-1_RZL8BGBM

Photo Credit #6: 742680 at https://pixabay.com/photos/chalkboard-story-blogging-believe-620316/

Photo Credit #7: Christina at https://unsplash.com/photos/LQ1t-8Ms5PY

Four Lessons in Time Management: What Graduate School Taught Me about Time Management

three round analog clocks and round gray mats

I am a Type-A personality who likes to do a variety of different activities yet cannot help but give each of them my all. Through this, I have learned a ton about time management. In particular, from 2017 to 2019, I was in graduate school at the University of Memphis while working as both a data scientist and a user researcher. I was easily working 70-90 hours a week.

Necessity is often the best teacher, and during this trial by fire, I figured out how to manage my time efficiently and effectively. Here are four personal lessons I learned for how to manage time well:

Lesson #1	Rest Effectively
Lesson #2	Work in Short-Term Sprints
Lesson #3	Complete Tasks during the Optimal Time of Day
Lesson #4	Rotating between Types of Tasks to Replenish Myself

Lesson #1: Rest Effectively

Developing an effective personal rhythm in which I had time to both work and relax throughout the day was necessary to ensure that I could work productively.

When many people think about time management (or at least when I do), they often focus on strategies/techniques to be productive during work time. Managing one’s time while working is definitely important, but I have found that resting and recuperating effectively is by far the most important single practice to cultivate to work productively.

Developing an effective personal rhythm in which I had time to both work and relax throughout the day was necessary to ensure that I could work effectively.

woman doing yoga meditation on brown parquet flooring

Several different activities help me relax: taking walks, exercising, hanging out with friends and colleagues, reading, watching videos, etc. People have a variety of ways to relax, so maybe some of those are great for you, and maybe you do something else entirely.

Generally, to relax I chose an activity that contrasted and complemented the work I had just been doing. For example, if my work was interviewing people – which I did frequently as a user researcher – then I would unwind with quiet, solitary tasks like walking or reading, but if my work was solitary like programming or writing a paper, I might unwind by socializing with others. Relaxing with a different type of activity as my work would allow me to rest and rejuvenate from the specific strains of that work activity.

I have seen a tendency in some of U.S. work/business culture to constantly push to do more. The goal is usually productivity – that is to get more done – and it makes sense to think that doing more will, well, lead to getting more things done.

That is true to a point, though, or at least to me. There comes a point when trying to do more actually prevents me from getting more done. Instead, taking enough time to rest and recuperate unwinds my mind so that when I am working, I am ready to go. This leads to greater productivity across all counts:

Quantitatively: I can complete a greater number of tasks
Qualitatively: The tasks I complete are of better quality
Efficiency: It takes me a lot less time to complete the same task

I think the idea that doing more work leads to greater productivity is a major false myth in the modern U.S. workforce. Instead, it leads to overwork, stress, and inefficiency, stifling genuine productivity.

Self-care through incorporating rest into my work rhythm has not only been necessary for my mental health but also to be a productive worker. In discussions around self-care, I have often a juxtaposition between being more productive and taking care of oneself, but those two concerns reinforce each other not contradict each other. Overworking without taking enough time to recuperate prevents me from being an effective and productive human worker. Instead, the question is how to cultivate life-giving and rejuvenating practices and disciplines so that I can become productive and maintain so.

Lesson #2: Work in Short-Term Sprints

I developed a practice of completing tasks in twenty-five-minute chunks. I would set the timer for twenty-five-minutes and work intensely without stopping on the given task/project until the time was up. (My technique has some similarities with the Pomodoro Technique, but without as many rules or requirements.) I realized that twenty-five-minutes was how long I could mentally work continuously on a single task without thinking about something else or needing a break. After that time, I would start to get tired and inefficient, so giving myself a break would let me unwind and rejuvenate.

After one of these twenty-five-minute sprints, I would take a break of at least five minutes: walk around, watch an interesting video, go talk with a colleague or friend, whatever I needed to do to unwind. These breaks were the time my brain would need to process what I was doing and reenergize for the next task. Given that my day would be made up of several of these twenty-five-minute sprints, for the first one or two, I might take a five minute break, but a few more, I might take a longer break as I had done more to unwind from.

A crucial skill for this practice has been successfully breaking down the given project to complete in the timed chunks. For some projects, I would designate a short-term task or goal to complete in the twenty-five-minutes. With my course readings, for example, I generally had to submit a summary and analysis of the readings. Thus, my goal during each twenty-five-minute sprint would be to finish one article or chapter – both reading it and writing the summary and analysis. I would start by reading the most significant subsections, generally the introduction and conclusion, summarizing and analyzing it as I read. That generally took up half of my twenty-five-minutes, so in whatever remaining time I had left, I would read the remaining sections.

This provided enough time to get a sense for the reading’s argument and complete the assignment, even in the off-chance that I did not have time to finish reading the entire article. In only twenty-five-minutes, I would knock out a whole reading, including my summary and analysis: one less task to worry about. Spending twenty-five-minutes a day is not that much of a burden either. Doing this, I would complete all the readings for my courses within the first few weeks of the semester, opening time over the next several months when my other work would pick up.

I could not split all activities into short-term tasks to complete in twenty-five-minutes, though. For those I could not, the trick was to estimate how much time an overall task would take. For example, if my supervisor gave me a month to complete a project, I would then calculate how many twenty-five-minute slots I would need per day given how many total hours I would likely need to spend on the project.

Data science projects are notoriously nonlinear, meaning that I could just about never break them down into sets of twenty-five-minute tasks, but rather almost always had to just figure out how much total time to budget like this. The various parts of a data science project – like data cleaning, building the model(s), and then improving/refining said model – could take widely different amount of times to complete and often fed into each other anyways. The first data science projects were always the hardest to determine how long they would take, but after doing many of them, I developed an intuitive sense of how much time to budget.

toddler's standing in front of beige concrete stair

The fear of a blank page and resulting procrastination were major issues I had to overcome when working on a project. At the beginning of the project, before I had broken down the task and determined the best strategy for how to complete it, focusing could be difficult. If I was not careful, the stress of the blank page or complete openness of the new project could cause me to become distracted and want to do something else instead. In more extreme cases, this could lead to procrastinating in getting started at all.

To get my ideas on paper, during the first twenty-five-minute sprint of a new task, I would look through all my materials and brainstorm how I would complete the task. Through this, I would develop an initial to do list of items that I could do in the ensuing sprints. Even though my to do list almost always changed overtime, this allowed me to get started. The most important caveat was to make sure I did that planning session when I was able to handle such an open-ended task (something I discuss in more detail in Lesson #3).

I also addressed my tendency to procrastinate by creating my own stricter deadlines for when a project was due. Extreme procrastination (like putting off starting or completing something until the last minute when you must rush to complete a task in the last several hours before its deadline) would destroy my productivity. Having to work in a mad rush would prevent me from having the balance between work and rest I discussed in Lesson #1 necessary to work productively. And when I have a lot of tasks, rushing last minute for one project would prevent me from working ahead on future projects, which would have then caused me to fall behind on them and create a vicious cycle of procrastination.

Thus, I would set my own deadline a week or two prior to a project’s actual deadline. For example, if I had four weeks to write an assignment, I would set my own deadline of three weeks for a presentable draft, and no matter what, I would meet this deadline. I would treat this like my actual deadline and never missed it. This presentable draft may not be perfect or amazing yet but something that in a pinch I would feel comfortable turning in: a solid B or B- quality version, not the A or A+ awesomeness my perfectionist self prefers. I might need to proofread once or twice to smooth out some kinks, but it has all the basic components of the task or assignment done. That way, if I became too busy with other projects to do that proofreading, it was good enough quality that I could still turn it in without editing in a pinch.

In the remaining week, I would then work out those minor issues, combing it a few more times to make it top quality, but if another, higher priority project or issue arose during that final week needing more of my attention than I anticipated, I could still have something to turn in. By making sure I stayed ahead with an adequate draft, I never had to worry about falling behind and rushing to finish as assignment last minute, and being a week or so ahead provided a cushion or shock absorber to handling any unforeseeable issues without falling behind. Through this, I never missed a single deadline despite working multiple jobs and being a full-time student.

Lesson #3: Complete Tasks during the Optimal Time of Day

I have found that certain types of activities are easier for me during certain times of the day. For example, being a morning person, I do my best work first thing in the morning. Thus, I would perform my most open-ended, creative, and strategic types of tasks – like brainstorming and breaking down a new project, solving an open-ended problem, and writing an essay or report – then. In the early afternoon, I would try to schedule any meetings and interviews (if that worked in the other people’s schedules as well of course), and in the late afternoon and evening, I would complete more menial, plug-and-chug aspects of a project that need less intense mental thought and more rote implementation of what I came up with that morning, like writing the code of an algorithm I had mapped out in the morning or proofreading a paper I already wrote. This would ensure that I would be fresh and efficient when doing the complex, open-ended tasks and not wasting my time and energy trying to force myself to complete such tasks during the times of the day when I am naturally tired, slower, and less efficient.

Lesson #4: Leveraging Different Types of Tasks to Replenish Myself

As both a data scientist and anthropologist, I have had to do a wide variety of tasks, using many different skills, ranging from talking and interviewing people to math proofs and programming to scholarly and non-fiction writing. This variety has been something I could use to replenish myself. Each of these activities is in of itself stimulating to me, but doing one of them exclusively for long periods of time would become draining after a while.

In agriculture, certain crops use up certain nutrients in the soil (like corn depletes nitrogen particularly strongly), so farmers will often rotate between crops to replenish the nutrients in the soil from the previous crop. Likewise, I found rotating between several different types of activities helpful for rejuvenating and replenishing my mind from the last activity.

If I had to do a series of very logical tasks like math or programming, I might replenish with a social task as my next activity like interviewing or meeting with people, or if I interviewed people for several hours, I would next break from that by doing something solitary like programming or writing. I would use these rotations strategically to rest from one activity while still practicing and developing other skill sets.

Conclusion

These are the lessons I learned for how to sustain myself while working 80-100-hour weeks. The first lesson was crucial: developing an effective rhythm between work and rest that enabled me to work productively, efficiently, and sustainably. The other three were my specific strategies for how I created that rhythm. I developed and refined them during intense, busy periods of my life in order to still produce high quality work while maintaining my sanity. Hopefully, they are helpful food for thought for anyone else trying to develop his or her own time-management strategies.

Photo credit #1: Karim MANJRA at https://unsplash.com/photos/dtSCKE9-8cI

Photo credit #2: Jared Rice at https://unsplash.com/photos/NTyBbu66_SI

Photo credit #3: Carl Heyerdahl at https://unsplash.com/photos/KE0nC8-58MQ

Photo credit #4: Allie Smith at https://unsplash.com/photos/eXGSBBczTAY

Photo credit #5: NeONBRAND at https://unsplash.com/photos/KYxXMTpTzek

Photo credit #6: Alex Siale at https://unsplash.com/photos/qH36EgNjPJY

Photo credit #7: Jukan Tateisi at https://unsplash.com/photos/bJhT_8nbUA0

Photo credit #8: Ksenia Makagonova at https://unsplash.com/photos/Vq-EUXyIVY4

Photo credit #9: Dawid Zawila at https://unsplash.com/photos/-G3rw6Y02D0

Photo credit #10: Dennis Jarvis at https://www.flickr.com/photos/archer10/3555040506/