The secret sauce of data science management

on YouTube ↗54m

" summary

Concrete practices that decide whether this is worth watching: grew team from 2 to 11 in 4 years while delivering models that move fraud‑prevention and customer‑experience metrics; an explicit project playbook with model sign‑off and silent A/B release; recurring mission teams, data‑science rubrics for leveling, monthly one‑on‑ones with input and development goals, SBI feedback, hackathons and a guarded research track, monitoring dashboards with retrain rules, and examples of what worked and what didn’t.

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" chapters (24)

1. 0:00Start
2. 2:39What Does It Mean To Be a Successful Data Science Manager
3. 4:43What Does a Successful Data Science Manager Look like
4. 5:28How Do We Measure a Data Science Manager
5. 5:55Where Do I Spend My Time
6. 6:28The Growth Mindset
7. 14:39Define Goals
8. 18:11Balancing between Research and Delivery
9. 21:15Weekly Team Meetings
10. 22:53Quarterly Retrospective Planning
11. 29:41What Can We Do To Proactively Avoid a Conflict like this with Partners
12. 30:09Creating Trust and Alignment
13. 30:36The Project Playbook
14. 31:38Project Prerequisites
15. 33:01Deep Customer Empathy
16. 34:14The Customer Problem and the Ideal State
17. 35:54Tips on Working with Partners
18. 37:08Meeting Summaries
19. 37:48Spotlight of Recognition
20. 41:25How Can You Help Your Manager Succeed
21. 43:41Summarize the Data Science Manager's Role
22. 45:11Do You Think Technical Knowledge Is Inevitable for a Good Data Science Manager
23. 51:15What's the Biggest Mistake You Made When You Started Out as a Manager
24. 52:32Is There a Tension between Time Spent Developing Goals Making Plans and Reviews Etc and Time Spent Doing Applied Data Science Work

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