«How do you develop good procedures around testing or how do you drive experimentation in a product or business setting?»

Carl Johan Rising works as Director of Data at Too Good To Go, a marketplace that enables food businesses to sell their surplus food instead of throwing it in the bin.

We talked about how to form a product team, and how to rethink the role of Data Scientists in your team, shape it in an embedded team, close to domains and with expertise and customer focus. We talked about skills, product focus, business partners and much more.

«(A career in) data gives you a bit of everything.»

• Data is a nice intersection between aspects of business, academia, physiological problems, and technical challenges.
• Business - especially understanding and decision making 
• Academia - working with hypothesis

Data at Too Good To Go

• If you look into how you want to use data to really drive decisions, it becomes more of a change management challenge, and not just a technical challenge
• «Start with a proper infrastructure foundation - a good clean data model»
• «Foundation building is invisible, and doesn’t by itself bring business value»
• The business sees the data team as one unite, without distinction between different capabilities in the team - Therefore the expectations are different
• «Make it very explicit what people can do and what their capacity is.» - gain understanding business

Product Analyst:

• «And soon as you have any emphasis on product, its development, its iterations, then it makes sense to have Product Analysts.»
• Too Good To Go works with multiple Product teams, each with their own problem spec
• in a Product team - Product Manager, Designer, Engineering Lead, Engineers, Machine Learning Engineers, and Product Analysts embedded in the team
• Product Analysts in each team to drive good identification of problem spaces and to enable the teams to do rapid experimentation
• The role will ask the "how do we drive good?" and set an experimentation agenda - driven by the Product Analyst
• Emphasis is on statistical knowledge and technical skills.
• There are two main stakeholders for Product Analyst -> Engineering Lead and Product Manager
• Focus on gathering the best resources to tackle a problem
• What skills and experiences do you need in a PA role?
  • statistical knowledge
  • programming
  • understanding of tech. aspects
  • ability to explain results

«I think the role of Data Scientist can mean a lot of different things.»

• Be a bit more explicit about what the work is and what it entails
• Minimize the possible confusion between expectations on Data Scientists In a company

Data Analytics Business Partner

• An embedded role that is part of the business with co-ownership of the outcomes
• Through this partnership it is much easier to gather context if you work with the domain