Data Scientist, Onboarding

“You never get a second chance to make a first impression”, and in our mission to increase the GDP of the internet, the onboarding experience of new users is critical to that first impression. We are looking for a Data Scientist to work with our Onboarding team to provide a superior initial product experience for our newest Stripe users. The onboarding team must deftly lead our users through the process of signing up on Stripe, and make sure they are connected with exactly the right products, while adapting to their business model, needs, and risk profile.  

You will be partnering with the Onboarding team to ruthlessly minimize friction and user surprise, while ensuring we safely operate on their behalf in the financial ecosystem. We are looking for a Data Scientist who is passionate about establishing essential data foundations, driving product decisions through data insights, and measuring impact through experiments and causal inference.

You will:

• Use data, experiments, statistical inference, and optimization to help the Onboarding team simultaneously achieve growth goals while minimizing undesired forms of risk
• Build measurement and observability around user conversion, the user funnel, and product adoption during onboarding
• Leverage experimentation and causal inference methods to identify drivers of user conversion and improve the onboarding process from both Stripe’s and our users’ perspectives
• Work with the Risk Product team to measure user compliance as well as our users’ onboarding experience
• Drive the collection of new data and the refinement of existing data sources
• Create onboarding analyses that tell a “story” focused on insights, not just data

We're looking for someone who has:

• 3-5+ years of product data science experience 
• Experience leading data-driven projects from definition to execution, driving impact and influencing product decisions and roadmaps
• A PhD or MS in a quantitative field (e.g., Statistics, Economics, Sciences, Engineering, CS)
• Expert knowledge of a scientific computing language (such as R or Python) and SQL
• Strong knowledge of statistics and experimental design
• Ability to communicate results clearly and a focus on driving impact