Data Science Manager

Details

Who We Are

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. Stripe’s mission is to increase the GDP of the internet and put the global economy within everyone’s reach.

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 hierarchical time series and agentic forecasting tools that predict payment volumes and revenue margins, as well as the governed metrics platform that feeds company-wide dashboards and executive reporting.

The team partners closely with Finance and Strategy, go-to-market, and Product stakeholders to inform financial decisions across Stripe’s business. It combines technical depth, strategic thinking, and executive partnership to develop both technical and business expertise.

Responsibilities

• Drive the roadmap and priorities for the team and work with Stripe leaders across the company to enhance data-driven decision-making.
• Collaborate with stakeholders across engineering, analytics, operations, finance, and marketing.
• Lead and manage processes that 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 development.
• Recruit and onboard 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.
• Participate deeply in modeling and design processes while coaching, mentoring, and leading the team.
• Work with data scientists, analysts, and engineers to create technical solutions and communicate effectively across teams and senior leadership.

Requirements

• PhD, MS, or BS in a quantitative field such as Statistics, Operations Research, Economics, Computer Science, or Engineering.
• At least 3 years of direct management experience leading data science or machine learning teams.
• At least 10 years of overall data science experience.
• Demonstrated expertise in designing metrics and guiding business decisions with data.
• Technical expertise sufficient to provide clarity to staff and senior scientists on architecture and strategic modeling decisions.
• Experience managing teams that have built and shipped machine learning systems and data products at scale.
• Hands-on experience with challenging data science problems.
• Strong cross-functional collaboration, rigorous thinking, and decision-making skills.
• Clear and persuasive written and verbal communication skills.
• Ability to thrive with a high level of autonomy and responsibility.
• Commitment to fostering a healthy, inclusive, challenging, and supportive work environment.

Preferred Qualifications

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