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Interview with a Data Scientist – Vicky Boykis

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It gives me great pleasure to interview Vicki Boykis – we’ve chatted a lot on Twitter over the past few years and her blog/ side projects have been inspiring for my own.

3. What do you wish you knew earlier about being a data scientist?
That it’s a lot of gruntwork. You’re going to spent maybe 10-20% of your time doing the stuff everyone talks about: picking models, doing machine learning, etc. Most of the time it’s, how do I get this matrix of data from one place to another. You have to decide if figuring out why stuff doesn’t work, all the time, in different ways, is something you’re interested in.

4. How do you respond when you hear the phrase ‘big data’?
With terror, because it means hashtags about deep learning and AI winter will soon follow.

5. What is the most exciting thing about your field?
If you play your cards right, you can impact the way a company operates. That’s always super interesting to me.

6. How do you go about framing a data problem – in particular, how do you avoid spending too long, how do you manage expectations etc. How do you know what is good enough?
My 9th grade English teacher made us write stories using vocabulary words we used that week, and he said that constraints makes us better writers because we’d have to be more creative. I like that agile enforces order in that you have 2 weeks to get x or y done. If it’s not done by the end of two weeks, we either refine or move on. I don’t like to spend too long once we figure out the general thrust of the problem because otherwise you just get mired in trying to model something that’s often too complex to model. I like to generate an idea or model and continue to iterate on it. There was a good podcast on this recently on Linear digressions.
7. How do you feel we’re doing in terms of diversity and inclusion in data science?

There was a really good quote about diversity, and I’m sorry to say I don’t remember who said it, but the quote was something along the lines of, if you have to talk about how a scientist is a woman, we don’t have diversity yet. Diversity means the ability to do your job as a woman or minority and not have it seem extraordinary or have articles talk about the fact that you’re a woman and not a scientist. We’re still a ways away from that, but I think a lot of factors, particularly the Python community, which is my home base, and which I love, does a great job at pushing us forward, closer to that goal.


Source: https://peadarcoyle.com/2018/09/10/interview-with-a-data-scientist-vicky-boykis/



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