Data Science in the Balanced Team

First presented at PyCon Ireland 2016

The goal of a Balanced Team is to share ownership and responsibility for the success of a project between team members. Each team member has specific obligations to the team and a specific area of authority. Until recently, designers, product managers and developers were the usual team members considered. In this talk I explore how data scientists can function in a balanced team and discuss my experience working as a data scientist on balanced teams at Pivotal Labs with our global clients. I consider what obligations and authority a data scientist can provide as part of a balanced team and how this situation differs from the usual jack-of-all-trades type data science work. I outline specific examples where data science can help user centric design and product management, and where the practices of lean-startup and agile development can help accelerate analysis and data science. Based on my experience building data science driven products with a global bank and European car manufacturers, I describe what we tried, what worked and most importantly what didn’t.
If you are a data scientist or need to work with one, this talk will equip you to understand how data science can be an integral part of a balanced team.

Transcript

1. Data Science in the Balanced Team Ian Huston
2. Who am I? Data Scientist at Pivotal Labs @ianhuston http://www.ianhuston.net Started working with data as an academic...
6. Balanced Team Shared Responsibility Act in service to the team Each role has obligations and an authority No more hero designer or PM as CEO More: Janice Fraser video http://tinyurl.com/jfraser http://www.slideshare.net/clevergirl/2015-balanced-teams-product-management-engineering
7. Design in a Balanced Team “Empathizer-in-Chief” Obligations to the Team 1. Understand the customer at an expert level 2. Translate high-value needs into product 3. Hone your craft 4. Facilitate balance within the team One Important Authority Prioritize customer problems http://www.slideshare.net/clevergirl/2015-balanced-teams-product-management-engineering
8. “[Y]ou need data thinking to be part of the culture and top of mind, not an after-thought.” https://medium.com/art-marketing/data-literacy-product-design-and-the-many-faced-god-cf8339e035a#.i8ry0xhqv
9. Things that worked
10. User Research + Data Exploration
11. Enabling PM to understand DS
12. Involving the whole team in data science process
13. Data Science + Dev pairing
14. Things that did not work
15. Single Dev + DS backlog
16. Arriving late to a project
17. Being part of multiple teams
18. Being (seen as) the magic bullet
19. Data Science in the Balanced Team “The Voice of Data” Obligations 1. Provide deep understanding about the available data and identify potential valuable uses/techniques. 2. Guard against unjustified, unethical or inappropriate uses of data. 3. Begin and continue collection of data to support future product goals. 4. Facilitate balance in the team. One Important Authority Bring data to every product conversation
20. Data Science in the Balanced Team Make data a central part of the product conversation. Provide data insights and possibilities in service to the team. Break down walls between data scientists and designers & developers. Data Science @ianhuston