Data Science Manager, Credit Risk

Enable Stripe’s growth and mitigate credit risk with modeling, data, and experiments

We’re working on making the global financial system programmable. This is one of the largest opportunities for impact in the history of computing, on par with the rise of modern operating systems.  Enabling the realization of this opportunity and simultaneously controlling our credit risk exposure, the Credit Risk team plays a critical role in the company’s financial health. 

We’re looking for an experienced data science leader to partner with the Credit Risk team as well as our Merchant Intelligence and Treasury teams to drive the use of data and modeling to measure and limit our credit risk, ensure high-quality decisions, and point towards future opportunities. The ideal candidate has experience in credit risk modeling, thinks creatively about measurement that leads to actionable outcomes, and values rigor in experimentation and modeling. Additionally, they communicate effectively with a variety of stakeholders and love leading teams and managing people. 

You will:

• Partner with Risk and Merchant Intelligence leadership to set a vision for credit risk modeling at Stripe as well as the develop of credit risk interventions and detections
• You and your team will:
• Develop statistical and machine learning models as well as simulations to measure the full distribution of credit risk outcomes and detect potential credit risk
• Design fully automated systems that capture risk across millions of users in 120+ countries
• Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
• Evolve our risk metrics, the datasets to support them, and the measurement of causal impact of initiatives to improve them
• Develop and communicate the metrics narrative to Risk leaders as well as company leadership
• Shape and influence our data models and instrumentation to generate insights and develop new data products and models
• Lead, recruit and grow data scientists and data analysts, creating a healthy and high- performing team

You’d ideally have:

• 7+ years of data science/quantitative modeling experience, including at least 3+ years of management experience 
• 3+ years experience in credit risk modeling 
• A PhD or MS in a quantitative field (e.g., Statistics, Economics, Sciences, Engineering)
• Expert knowledge of a scientific computing language (such as R or Python) and SQL
• Expertise in statistics and experimental design
• Ability to communicate results clearly including with senior executives