Big data scientist interview questions

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Everybody wants to hire a data scientist these days. According to read write the role is overhyped and overpaid. Hype aside, what’s a good approach to interviewing these hard to find people?

Here’s Read Write’s guide. Also Hilary Mason has an interview guide. Also take a look at Chris Pearson’s data scientist hiring guide.

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While you’ll surely have technical questions to ask, we figure you may already have a handle on those. They’ll vary from business to business.

What we’ve put together is a series of questions that we hope will tease out some good stories, and underscore a candidates real-world experience. These are are also great for the cross section of folks involved in the hiring process, higher level managers, HR & recruiters, plus technical folks that may have data near & dear to them.

1. What’s common?

What key metrics do you see firms repeatedly missing? Why are they important?

You’ve worked as data scientist before, and run into a lot of problems at different firms. Inevitably, some of those repeat themselves. Give an example of a metric you see over-and-over, that’s essential, but often missing attention.

Also: Is the difference between dev & ops a four-letter word?

2. What’s your favorite?

What is your favorite KPI and why?

As a data scientist, you’ve probably approached different companies, and found a couple of indicators that you particularly like. Maybe they highlight potential for growth? Or lead to other interesting discoveries about the business?

Related: Is automation killing old-school operations?

3. Let’s talk dollars

Give an example of a financial benefit you brought to a firm. How & how much?

Give an example where a measurement you made, and a business change it informed had real ROI for the business. What was that discovery? How did the business make the change? What was the financial benefit to the bottom line?

Read: Do managers underestimate operational cost?

4. Business data discovery

Give an example where you discovered data the business didn’t know it had. What & How?

Sometimes businesses have assets stored, that have been forgotten. Perhaps they’ve been archived, or a collection job has been forgotten. Perhaps it’s a corner of salesforce that hasn’t been evaluated. How did you bring the new data to light, and make use of it?

Also: Is the difference between dev & ops a four-letter word?

5. Why do you love data?

Why is data scientist your chosen career path?

This is an open ended question, but should spark some stories. Perhaps the candidate enjoys working with tech, product & biz-ops equally? Why are your skills uniquely suited to the role over other technical careers?

Also: Is the difference between dev & ops a four-letter word?

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