Data Scientist, Stripe Capital

  • Stripe
  • New York, NY, USA
  • Dec 02, 2019
Full time

Job Description

Many of the millions of businesses on Stripe have trouble accessing the capital they need to grow. Stripe Capital aims to change that. We combine Stripe’s proprietary data with sophisticated modeling to offer businesses on Stripe fair, affordable, and transparent financing. Though still in its early stages, Capital has emerged as one of Stripe’s most promising products.

We’re looking for talented data scientists to join the Capital team to help us better understand our users so we can scale Capital to support more users, new financial products, and new markets. If you are an expert working with data to forecast performance and credit risk, and excited to apply your experience to build new financial products, we want to hear from you..

You will:

  • Work closely with product, business, credit risk and engineering teams to conduct analyses and develop machine learning models to support new lending products
  • Design forecast methodology and credit risk management strategy to support loans and merchant cash advance products
  • Design, analyze, and interpret the results of experiments of different credit risk strategies, to effectively manage exposure, yield and loss
  • Apply statistical and analytical approaches on large datasets to (1) measure results and outcomes of our current models and credit risk strategies, (2) understand the impact of eligibility rules on credit risk and revenue
  • Drive the collection of new data and the refinement of existing data sources to enhance our credit risk management framework

You’d ideally have:

  • A Ph.D. or M.S. in a quantitative field (including, but not limited to, economics, mathematics, statistics, and computer science)
  • 3+ 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, Pig, etc.)
  • The ability to communicate results clearly and a focus on driving impact

You should include these in your application:

  • A resume and LinkedIn profile
  • A description of the most interesting data analysis you’ve done, the key findings, and the impact of the analysis
  • A sample of code you’ve written related to data analysis and machine learning models