Data Scientist (Risk)

We are building out a world class data team within our Risk division and it's the opportunity to join a team as we embark on an incredible 3 year scale up. These are newly created roles, working with great leadership and a chance to have a real and tangible impact on our business.

You probably want to know what's involved?

Stenn is democratizing access to capital for SMEs and companies in emerging markets. You're getting in at the ground floor of the newly created Decision Science team to help shape Stenn's financial products in fundamental ways. There is a lot of buy-in from Management, because they believe innovative and impactful machine learning solutions are required to drive Stenn's growth to new heights. In more detail:

• You will develop roadmaps for areas of work, scope related projects, and drive execution primarily through individual contribution and also by drawing on other team members
• Besides ML, you will determine the best tools to use for each problem, whether it requires heuristic rules, inferential techniques, or advanced machine learning

How will we measure success in this role?

• Success will be measured in terms of your contribution to a highly performant model-driven risk management architecture.
• Impact on Business Results: the ability to deliver high-impact solutions that drive business growth and profitability.
• Technical Excellence: technical excellence in data science (in particular analytical ability, statistical rigor) and the ability to deliver high-quality code

How do you know if you are the right candidate?

• You consider yourself a generalist, full-stack data scientist who is comfortable and excited about working in a small team
• You have experience in a commercial data science setting (fintech, e-commerce, etc.)
• You can seamlessly collaborate with teams across engineering, product, and business functions
• You communicate very well with both technical and nontechnical partners.
• You are well-versed in Python and SQL
• You have prior experience in a commercial data science setting (fintech, e-commerce, etc.)