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Master Data Science Management: Agile ML, Debrief Culture, Metrics & Scale to Production
Open original DataTalks.Club episode
Master Data Science Management: Agile ML, Debrief Culture, Metrics & Scale to Production
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Episode Overview
How do you run data science teams so experiments become reliable, measurable products? In this episode, Shir Meir Lador, a data science group manager at Intuit who builds machine and deep learning models for document intelligence in TurboTax and QuickBooks, walks through practical approaches to data science management and agile ML.
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Chapter Summary
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- 1:40 - Episode Introduction: The Secret Sauce of Data Science Management
- 2:40 - Career Background: Electrical Engineering to Document Intelligence at Intuit
- 4:31 - Military Leadership Lessons: Pilot Training & Debrief Culture Origins
- 5:24 - Debriefing Practice: Pre/post Focus Areas for Continuous Improvement
- 9:18 - Group Manager Role: Strategy, Mentoring, Standards and Roadmaps
- 11:53 - Measuring Success: Business Impact and Team Engagement Metrics
- 12:56 - People Metrics: Pulse Surveys, Manager Score and Skip-level Feedback
- 16:19 - Leadership Pillars: Vision, Driving Results, Building High-performance Culture
- 17:23 - Managing Leadership Relationships: Communicating Vision and Securing Resources
- 24:24 - Team Development: Goal-setting, One-on-ones, Feedback and Recognition
- 26:25 - Goal Alignment: Cascading Roadmap Goals to Individual Development
- 32:00 - Fostering Innovation: Hackathons, Paper Clubs and Learning Forums
- 34:31 - Cross-Functional Integration: Product Partnerships and Expectation Management
- 41:06 - AI Project Uncertainty: Data Risks, Unknowns and Rapid Experimentation
- 44:18 - Agile for ML: Two-week Sprints, Exploration Tasks and Grooming Practices
- 45:36 - Scoping ML Work: Exploration Sprints, Design Stories and Iterative Milestones
- 49:54 - Core Manager Skills: Communication, Strategic Clarity and Growth Mindset
- 54:59 - POC to Production: Customer-focused Metrics, A/B Testing and Incremental
- 58:18 - Resources & Further Reading: Shir’s Talks and Blog Posts