Am I a data scientist?

Transcript

1. Am I a data scientist? Alyssa Frazee, Stripe @acfrazee

2. © 2009 Lisa Slavid

3. statistician a data scientist © 2009 Lisa Slavid

4. Where I’m coming from Math undergrad Biostatistics PhD “Machine Learning

   Engineer” today Recurse Center (née Hacker School) 2010

5. Am I a data scientist?

6. Am I a data scientist? What do I really mean

   by this question?

7. Am I a data scientist? What do I really mean

   by this question? Could I get a job offer with a title of “data scientist?”

8. Am I a data scientist? What do I really mean

   by this question? Am I preparing my students to be able to get job offers with a title of “data scientist?”

9. Am I a data scientist? What do I really mean

   by this question? Could I get a job offer with a title of “data scientist?” → sometimes implicitly industry → and sometimes specifically tech

10. What’s “data science”?

11. None

12. data skills spectrum

13. theoretical statistics software engineering

14. theoretical statistics software engineering data science

15. understanding quantitative data building a product data science

16. output: numerical results output: usable software data science

17. Am I a statistician? points for: • Am in a

    grad program called [bio]statistics • Know things about martingales and the delta method • Can explain what a p-value is and interpret linear regression coefficients points against: • Haven’t proved a theorem since 2011 • Spend more time writing bash scripts than inventing estimators • No publications in statistics journals

18. Or am I a data scientist? points for: • Can

    program in more than one language • Actively use git & GitHub • Have written R packages and reproducible reports • Once made a web app and also a D3.js graph points against: • Not working in industry • Have never written a SQL query more complicated than select * from table • Understanding of Hadoop, Spark, and AWS is vague at best • Have never written production code
19. None

20. Idea! I will listen to what experts in our field

    say! Camp #1: Data science is just a rebranding of applied statistics. Camp #2: Statistics and data science are overlapping. Neither is a subset of the other. Camp #3: Statistics is irrelevant to data science.
21. None

22. First: do I want to be a data scientist?

23. Second: Does it matter?

24. Am I on the job market? Am I hiring?

25. If you decide it matters: some distinguishing features

26. Intentionality about programming

27. Intentionality about programming Spending time thinking primarily about: • code

    efficiency • version control • code quality (cleanliness, modularity) • documentation / usability • unit testing • systematic debugging • giving and receiving code review • and other principles of software engineering

28. Interest in schleppy- but-practical projects

29. Interest in schleppy- but-practical projects • figuring out how to

    get the data you need • combining existing tools/methods in new ways • finding the simplest solution that works in practice

30. Focus on concrete decision-making

31. Focus on concrete decision-making less about inference and parameter estimation,

    more about what action should be taken

32. Camp #1: Data science is just a rebranding of applied

    statistics. Camp #2: Statistics and data science are overlapping. Neither is a subset of the other. Camp #3: Statistics is irrelevant to data science.

33. Perspective from the other side Camp #1: Data science is

    just a rebranding of applied statistics.

34. Perspective from the other side Camp #1: Data science is

    just a rebranding of applied statistics. Intentionality about programming

35. Perspective from the other side Camp #1: Data science is

    just a rebranding of applied statistics. The day-to-day work is different!

36. Perspective from the other side Last month I: • wrote

    Ruby, Scala, Coffeescript, and Python • fought with maven • backfilled some busted tables in our databases • investigated the mystery of why some of our cluster boxes are overworked • learned how to be on call (so I can fix some of Stripe if it breaks at 3am) • helped teach a SQL class • and did some statistics

37. Camp #3: Statistics is irrelevant to data science. Perspective from

    the other side

38. Camp #3: Statistics is irrelevant to data science. Perspective from

    the other side

39. Statistics and data science are overlapping. Neither is a subset

    of the other. Perspective from the other side

40. About that identity crisis: Program intentionally and be a data

    scientist, if you want!

41. About that identity crisis: Or don’t! Statistics is hugely important

    and relevant in its own right!

42. • http://andrewgelman.com/2013/11/14/statistics-least- important-part-data-science/ • http://bulletin.imstat.org/2014/09/data-science-how-is-it- different-to-statistics%E2%80%89/ • https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the- 21st-century/ •

    http://datascopeanalytics.com/blog/what-is-a-data-scientist/ Further reading: