Big Data

Be a data scientist for the love of the craft not the perks

Data science is a hot field, but it's not a good career choice for everyone. Find out what makes a good data scientist.

Photographer: Andrey Popov

We're a bit spoiled in Silicon Valley. Not only do we have great weather and friendly people, but we also seem to be the epicenter of the data science career frenzy, where an average science geek can live a really good life.

Many people dream of working as a data scientist at a great company such as Google or Facebook, bringing home a good salary, and enjoying the perks of a thriving, employee-centric firm; however, there's more to life than a nice salary and an onsite barbershop. If you go into data science just for the perks, that's a huge mistake. To be a successful data scientist, you need to love data science.

A data science state of mind

I was doing data science for fun before it was called data science. I come from a family of horseplayers and as a teen in high school I would spend my nights programming my TRS-80 with the latest algorithms for handicapping the next day's races. I loved it, and I still do.

Data scientists love to solve problems, write code, build charts and graphs, and work all night with others who love the same things. I'm not saying you should live to work, though work-life balance becomes a lot easier if you enjoy what you do. For good data scientists, it's not just a job, it's a state of mind — they believe they were born to do their job, and they feel fortunate they can make a good living at it.

It would be miserable to work as a data scientist if it's just a job. As a physicist or a mathematician, you may believe you're a good fit for data science, but if you're not accustomed to programming around the clock to hit a deadline you feel is unrealistic, the life of a data scientist may not suit you well. And as a computer programmer, you may feel you just need to dust off some of your college math books; however, if you don't have the patience for solving complicated math problems, data science may be the wrong path to pursue. Graphic artists seem to have the hardest transition. Yes, as a data scientist, you must know how to explain data through graphics, but data science is also a very analytic job. If you're not prepared to spend hours and hours by yourself just solving problems and writing code, this isn't the life for you.

The right person for the job

As a leader or a manager, it's important to hire the right people for the data scientist position. Some people may already have a sense they're not right for data science, and others may have a false sense of optimism. Either way, it's your responsibility to protect your organization and your interviewee from an improper fit. During the interview process, look for several things.

First, ask them about their hobbies and interests. There's nothing wrong with a potential data scientist who loves to skydive or play in a rock band. However, you should be able to draw the connection between data science and their lifestyle outside the workplace. For instance, I love gambling — not just on horses, but all kinds of gambling. When I'm not helping clients, you might find me on a craps table in Vegas or in a smoky room playing poker. When I'm not analyzing corporate data, I'm analyzing odds at a casino. It's easy to understand why I'm good at data science.

Another thing to ask about is the last few problems they've solved and how they solved them. In their response, you're looking for both their logic and emotion. A good data scientist will light up when they talk about problem solving. Instead of just rattling off facts and details, they'll tell you a story about the setup, their struggle, and how they overcame it. These are the kinds of people you want on your team. Their enthusiasm comes through just sharing their past problem-solving experiences — this is the same enthusiasm that you want applied to your issues.

Finally, have your interviewee hang out with your other data scientists. It's best if you get them out of interview mode and into more of a casual environment. Maybe grab some lunch or give them a tour of the campus. As your interviewee is socializing with your other data scientists, watch their body language and how they interact — it's difficult to hide feeling uncomfortable. Data scientists tend to have an instant rapport with each other. If you sense your interviewee may feel out of place, there's probably a good reason.


Data science can be an exciting career, but it's not a good fit for everyone. Many people like the idea of becoming a data scientist — until they find out what the job really entails.

If you love solving difficult math problems, writing code all night long, and spending endless hours building infographics and data visualizations, then by all means go for it. But, if I can talk you out of being a data scientist, then you shouldn't be one. Life is short — don't spend it trying to do something you don't enjoy.

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About John Weathington

John Weathington is President and CEO of Excellent Management Systems, Inc., a management consultancy that helps executives turn chaotic information into profitable wisdom.

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