Data Scientist, Risk

San Francisco, CA OR New York, NY OR Remote (North America)

Applications have closed

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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Stripe is the best software platform for running an internet business. We handle hundreds of billions of dollars every year for millions of businesses around the world. More than 80% of American adults bought something on Stripe in the last year.

With all this data, we’re looking for a talented data scientist to join the Data Science team to help us better understand our users, build better products, and optimize our operation. If you are data curious, excited about deriving insights from data, and motivated by having impact on the business, we want to hear from you.

You will:

  • Act as an embedded partner to the Risk team, helping them to identify and answer questions with data and modeling
  • Create analyses that tell a story focused on insights, not just data
  • Build statistical and/or machine learning models to understand the riskiness of our customers
  • Design, analyze, and interpret experiments
  • Build and improve data ETL pipeline to collect new data and refine the existing data sources

We’re looking for someone who has:

  • 5+ years experience working with and analyzing large data sets to solve problems and drive impact
  • A PhD or MS in a quantitative field (e.g., Operations Research, Economics, Statistics, Sciences, Engineering)
  • Expert knowledge of a scientific computing language (such as R or Python) and SQL
  • Strong knowledge of statistics and experimentation
  • Experience working with multiple cross-functional teams to deliver results
  • The ability to communicate results clearly

Nice to haves:

  • Prior experience in Trust & Safety, Risk or a related field

Tags: Economics Engineering ETL Machine Learning ML models PhD Python R Research SQL Statistics

Regions: Remote/Anywhere North America
Country: United States
Job stats:  89  5  0
Category: Data Science Jobs

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