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Data Science in the Balanced Team

41d2c569bbfbec97e0ab6fd2a8c261b7?s=47 Ian Huston
November 06, 2016

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.

41d2c569bbfbec97e0ab6fd2a8c261b7?s=128

Ian Huston

November 06, 2016
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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...
  3. None
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  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