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Are You Ready for Your Data Science Interview?

Keep it simple, Don’t Profess, Be Passionate

I went from looking for work in data science to screening potential candidates for positions within a development team in a relatively short period (under a year). It’s very illuminating being on the other side of the process. This article will cover some of my observations, and hopefully, it will assist you in your search for your first job in data science/engineering or help you find your next challenge.

Photo by LinkedIn Sales Solutions on Unsplash

How Good is Your SQL?

Machine Learning and AI are like caviar (a delicacy). SQL is the bread and butter. I should preface this by saying this won’t always be the case. I’m positive there are numerous positions where a deep understanding of ML and AI are required. However, it’s more probable that you (the data person) will have a customer whose data fluency doesn’t extend beyond a pivot table in excel. These people couldn’t care less about hyper-tuning parameters in your tree-based model. They’re about results. Unfortunately, the vehicle by which you’ll present data in many situations is an excel workbook with some pivot tables and “fancy” graphs. This means you’ll be regularly using some flavor of SQL to pull those extracts. This reality isn’t necessarily a bad thing. If your customer isn’t too stubborn, they’ll be open to new and ostensibly better ways to consume data. This situation is when your creativity will come into play. But let’s not get ahead of ourselves. How good is your SQL?

Don’t Overestimate Your Abilities

I participated in a last-minute technical interview for a senior middle-management position which became the catalyst for this article. The interviewee had a resume that reads well. My colleague began the discussion with a fundamental question regarding data, and the interviewee seemed perplexed. We quickly transitioned to the technical portion, which consisted of some reasonably tricky SQL problems. The interviewee essentially just tried writing random code. We ended the interview well within the allocated one hour. I handled the initial screening for potential candidates after this experience.

I added a question to the screening process. How do you rate your SQL abilities on a scale of 1–10? The answers were varied. Only one candidate had the requisite knowledge commensurate with their score, while everyone else overestimated their abilities. One candidate said their SQL was a 10. It didn’t turn out to be so. I now recall I overestimated my SQL skills before interviewing for my current position and was quickly humbled. Rate your SQL skills between 1–10 right now. Great, now subtract three. That’s where you probably sit. You have absolutely nothing to lose by perpetually improving your SQL no matter who you are or where you are in your career. This fact is especially relevant if you’re looking for your first job.

Is This Something You Love to Do?

Numerous folks want to work in data science for innumerable reasons. Is it something you love, or is it just a job? Working as a developer can be frustrating and thankless. People who haven’t written a line of code in their life will make flippant comments about how easy something should be. If this isn’t something you love to do, these situations will eat away at you. If you don’t want to learn continually, this isn’t the right field for you. Another question I ask candidates is: “What do you do outside of school or work to improve your skills?” One person said “nothing.” If you don’t have a portfolio of personal projects or a GitHub with your work on it, it would seem this isn’t a passion of yours. What you’ve learned isn’t as important as how you’ve applied what you’ve learned. This idea is essential for people trying to get a job right out of university. Your school projects may be impressive, but they were a requirement. Personal projects show initiative and a willingness to learn and try new things.

Be Ready

I can’t believe I have to say this. Be at your interview on time and have the ability to type. One candidate showed up to a technical interview for a senior position on an iPad. Don’t be a dummy; this is a horrible look regardless of your technical skills. Don’t try to “teach” or profess the interviewers about the code you’re reviewing or writing. Is someone going to recommend you for hire if you spent thirty minutes talking to them like they’re stupid? It would be best if you were confident. Don’t be arrogant.

Photo by Andrew Seaman on Unsplash

In Conclusion

Make sure you’re practicing SQL. Be on time. Be able to type, don’t be arrogant, be passionate.



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Brandon Smith

Brandon Smith


I’m fascinated with understanding the implications of asymmetries in data and network analysis. Pug dad. Brooklyn is the borough.