Project Managing in Data Science Teams

Explore the intricacies of managing data science projects in this insightful conference talk from code::dive 2019. Delve into Tereza Iofciu's personal experiences as a product manager for a cross-disciplinary data science team, following a machine learning project from conception to production. Learn valuable tips, tricks, and lessons for navigating the complexities of data science projects, including effective stakeholder communication, problem translation, and overcoming technical challenges. Gain insights into the often-overlooked aspects of implementing data products and bringing prototypes to production. Discover the importance of cross-team collaboration, user perspective consideration, and managing expectations in data science projects. This talk offers a practical guide to the challenges and essential communication skills required for successful data science project management.

Intro
Who is Tereza
What is fare calculator
Meeting the team
New meeting
Meeting minutes
Role of product management
User perspective
Working with other teams
Data scientists
Upper management
Data product
User perception
Product teams
Black box
Summary
Conclusion