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Study mode:
on
1
Intro
2
Who is Tereza
3
What is fare calculator
4
Meeting the team
5
New meeting
6
Meeting minutes
7
Role of product management
8
User perspective
9
Working with other teams
10
Data scientists
11
Upper management
12
Data product
13
User perception
14
Product teams
15
Black box
16
Summary
17
Conclusion
Description:
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.

Project Managing in Data Science Teams

code::dive conference
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