Data Science Manager, Finance and StrategyActive

The opportunity

Finance and Strategy Data Science builds the forecasting models, data infrastructure, and analytics tools at the core of how Stripe measures and plans its business. The team owns everything from hierarchical time series and agentic forecasting tools that predict payment volumes…

What you'll do

  • Drive the roadmap and priorities for your team, and work with many Stripe: leaders across the company to enhance our ability to be data-driven.

  • Collaborate with stakeholders across the organization such as engineering,: analytics, operations, finance, and marketing.

  • Lead and manage processes to help the team do its best work and engage effectively with the rest of Stripe.

  • Manage a high-performing team of data scientists, supporting them to achieve: a high level of technical excellence and advance in their careers.

  • Recruit and onboard great data scientists, in collaboration with Stripe's recruiting team.

  • Contribute to broad data science initiatives as a member of Stripe's data science management team.

What they're looking for

  • A PhD, MS, or BS in a quantitative field (e.g., Statistics, Operations: Research, Economics, Computer Science, Engineering)
  • You have at least 3 years of direct management experience leading data: science or ML teams, and 10 years of overall data science experience.
  • You've demonstrated expertise in designing metrics and guiding business decisions with data.
  • You have technical expertise to drive clarity with staff and senior: scientists about architecture and strategic modeling decisions.
  • You've managed teams that have built and shipped machine learning systems and: data products at scale, and have hands-on experience with challenging problems.
  • You work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs.
  • You have clear and persuasive communication skills in writing and in speech.
  • You thrive on a high level of autonomy and responsibility.