Data Science Manager

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.

About the Team

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 and revenue margins, to the governed metrics platform that feeds company-wide dashboards and executive reporting. We partner closely with Finance and Strategy, GTM, and Product stakeholders to directly inform financial decisions across Stripe's entire business.

What You'll Do

Data Science Managers at Stripe are responsible for the success of their team. You'll be deeply involved in the modeling and design processes as well as coaching, mentoring, and leading the team. You'll drive efficient data science teams, have a strong user focus, and communicate effectively across teams and senior leadership.

Responsibilities

• Drive the roadmap and priorities for your team, and work with leaders across Stripe to enhance data-driven decision making.
• Collaborate with stakeholders across 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 technical excellence and career progression.
• 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.

Qualifications

Minimum Requirements

• A PhD, MS, or BS in a quantitative field (e.g., Statistics, Operations Research, Economics, Computer Science, Engineering).
• At least 3 years of direct management experience leading data science or ML teams, and 10 years of overall data science experience.
• Demonstrated expertise in designing metrics and guiding business decisions with data.
• Technical expertise to drive clarity with staff and senior scientists about architecture and strategic modeling decisions.
• Experience managing teams that have built and shipped machine learning systems and data products at scale, with hands-on problem-solving experience.
• Proven track record of cross-functional work, rigorous thinking, and making hard decisions and tradeoffs.
• Clear and persuasive communication skills in writing and in speech.
• Ability to thrive with a high level of autonomy and responsibility.
• Commitment to fostering a healthy, inclusive, challenging, and supportive work environment.

Preferred Qualifications

• Experience working with geographically distributed teams.
• Expertise in time series forecasting, predictive modeling, or optimization.
• Expertise in data design and building scalable data architectures.