Data Scientist, Capital Management
Enable Stripe’s growth and optimize deployment of capital 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 ensuring we optimize the deployment of capital and maximize our profitability, the Capital Management team plays a critical role in the company’s financial health.
We’re looking for an experienced data scientist to partner with the Capital Management team to drive the use of data and modeling to deploy capital in the highest valued use cases, quantify capital requirements and efficiency, and identify areas for optimizing capital usage.
The ideal candidate has experience in statistical forecasting and mathematical optimization, thinks creatively about measurement that leads to actionable outcomes, and values rigor in data and modeling.
- Formulate optimization models and quantify uncertainty to drive business decisions related to the management of Stripe’s portfolio of users and products
- Develop statistical and machine learning models to forecast drivers of profitability and capital utilization
- Use data and models to design capital optimization strategies and interventions while preserving and improving the user experience
- Evolve our capital attribution frameworks, efficiency metrics and the datasets to support them
- Spin up proofs of concept for different applications and iterate to build scalable solutions
- Design fully automated systems that capture risk-adjusted returns and capital attribution across millions of users in 120+ countries
- Collaborate with cross-functional teams, particularly Finance, Risk, Sales and Engineering, and drive initiatives to bridge inefficiencies and generate compounding returns to deployed capital
- Shape and influence our data models and instrumentation to generate insights and develop new data products and models
You’d ideally have:
- 5+ years of data science/quantitative modeling experience, including 3+ years experience in forecasting and optimization
- A PhD or MS in a quantitative field (e.g., Operations Research, Quantitative Finance, Economics, Sciences, Engineering, Statistics)
- Strong understanding of mathematical optimization and stochastic modeling, and experience building and calibrating those models to fit specific business needs
- Strong working knowledge of SQL, R, Python, Matlab, C++, or equivalent.
- A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
- A familiarity with risk-adjusted returns (or curiosity to learn) in a high growth environment while maintaining a great user experience
- Ability to communicate results clearly and a focus on driving impact
At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Stripe, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us.