Data Scientist, Payment Intelligence

San Francisco, CA OR Seattle, WA

Full Time
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Posted 1 month ago

Build out rigorous observability and decision making across the many ways payments are optimized at Stripe

At Stripe, data science managers grow teams and inspire them to rigorous work that shapes our decisions and products. We’re looking for an experienced data science manager to lead our team supporting Payment Intelligence.

The Payment Intelligence group is responsible for optimizing each of the billions of dollars of transactions processed by Stripe each year on behalf of our users, in order to maximize successful transactions while minimizing payment costs and fraud. We own products like Radar, Adaptive Acceptance, and Chargeback Protection from end to end and work across the technical stack: from machine learning over our users’ data, to integrating ML intelligence and serving real-time predictions as part of Stripe’s payment infrastructure, to building user-facing product surfaces like dashboards and controls. We need your help in building out a culture of rigorous measurement, experimentation, and optimization.

You will:

  • Lead a team of data scientists and analysts to:
    • Define and measure key outcome metrics for our products + systems
    • Design and analyze experiments to improve the optimization systems at Stripe - ranging from products spanning fraud, authorization rates, and user costs
    • Apply statistical methods, causal inference, and predictive modeling to inform product decisions and optimize our products and systems
    • Build new (and expand existing) machine learning frameworks (which currently span Experimentation, Multi-Armed Bandits, Regression Trees, and Deep Learning) in order to stop fraud and optimize payments
  • Partner closely with product and engineering teams to identify and prioritize the most important data science projects
  • Recruit great data scientists and analysts, in collaboration with Stripe’s recruiting team
  • Develop data scientists and analysts on the team, helping them advance in their careers, providing them with continuous feedback

You’d ideally have:

  • 5+ years of data science experience; 2+ years of management experience 
  • A PhD or MS in a quantitative field (e.g., Statistics, Economics, Sciences, Mathematics, Engineering)
  • Expert knowledge of a scientific computing language (such as R or Python) and SQL
  • Strong knowledge of statistics and experimental design
  • Ability to communicate results clearly and a focus on driving impact
Job tags: Deep Learning Economics Engineering Machine Learning ML Python R SQL
Job region(s): North America
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