Data Scientist, Banking and Financial Products
Help build Stripe’s newest businesses
About our Team:
Stripe’s Banking and Financial Products group is building new products that expand the scope of problems we tackle beyond payments and into the rest of the financial stack. Right now this includes Capital, Issuing, Treasury, and Atlas - and there’s more on the way.
We’re looking for an experienced data scientist to partner with this team to dramatically improve our products and drive a science-driven culture.
- Work closely with PMs, engineers, and business partners to identify important data science questions for new B&FP products
- Develop highly-visible dashboards and automated reporting related to key performance metrics
- Design, analyze, and interpret the results of A/B experiments that span multiple Stripe product areas
- Develop statistical and machine learning models to optimize the product and user experience
- Shape and influence our data models and instrumentation to generate insights on new areas of opportunity and new products
We’re looking for someone with:
- A Ph.D. or M.S. in a quantitative field (including, but not limited to, economics, mathematics, statistics)
- 4+ years experience working with and analyzing large data sets to solve problems
- Expert knowledge of a scientific computing language (such as Python or R) and SQL
- Strong knowledge of statistics and experimental design
- Extensive experience in credit risk analysis and forecasting
- Some experience with tools for working with “big data” in a distributed fashion (Spark, Hadoop, etc.)
- The 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.