I delivered this keynote at the Fast Forward Labs Data Leadership Conference on April 28, 2016. You can find related materials in the following publications: https://www.oreilly.com/ideas/where-should-you-put-your-data-scientists http://firstround.com/review/doing-data-science-right-your-most-common-questions-answered/

1. Where should you put
your data scientists?
Daniel Tunkelang

2. Review: why you hire data scientists

3. To improve products

4. To improve decisions

5. Organizational structure matters

6. stand-alone
embedded
integrated

7. The stand-alone model

8. Pro: gives team autonomy

9. Pro: positions data as first-class

10. Con: risks marginalizing team

11. Con: other teams like self-sufficiency

12. The embedded model

13. Pro: ensures utilization

14. Pro: flexible allocation

15. Con: team resents lack of autonomy

16. Con: management challenges

17. The integrated model

18. Pro: organizational alignment

19. Pro: long-term investment

20. Con: dilution of data science

21. Con: lack of reuse

22. stand-alone: autonomy, data as first class
embedded: utilization, flexible allocation
integrated: alignment, long-term investment

23. stand-alone: marginalization, isolation
embedded: resentment, dual management
integrated: dilution, lack of reuse

24. You can mix and match

25. Adapt as company evolves

26. Remember the mission

28. Thank you.
Daniel Tunkelang
dtunkelang@gmail.com
: @dtunkelang