Data Scientist, Banking and Financial Products

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Stripe

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.

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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.

You will:

  • 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

Tags: A/B testing Banking Big Data Credit risk Economics Hadoop Machine Learning Mathematics ML models Python R Spark SQL Statistics

Region: Europe
Job stats:  40  10  0
Category: Data Science Jobs

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