Data Science Manager, Finance and Strategy

Details

Stripe is a financial infrastructure platform for businesses. The Finance and Strategy Data Science team builds forecasting models, data infrastructure, and analytics tools that support how Stripe measures and plans its business. The team develops hierarchical time series and agentic forecasting tools for predicting payment volumes and revenue margins, as well as a governed metrics platform for company-wide dashboards and executive reporting. The team partners with Finance and Strategy, go-to-market, and Product stakeholders to inform financial decisions across Stripe.

Data Science Managers are responsible for the success of their teams. The role involves participating in modeling and design processes, coaching and mentoring team members, and leading data scientists, analysts, and engineers in creating technical solutions and communicating effectively across teams and senior leadership.

Responsibilities

• Drive the roadmap and priorities for the team and work with Stripe leaders to improve 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 across 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.

Requirements

• At least 3 years of direct management experience leading data science or machine learning 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, including hands-on experience with challenging problems.
• Strong cross-functional collaboration skills, with the ability to think rigorously and make difficult decisions and tradeoffs.
• 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

• PhD or MS in a quantitative field such as Statistics, Operations Research, Economics, Computer Science, or Engineering.
• Comfort working with geographically distributed teams.
• Expertise in time series forecasting, predictive modeling, or optimization.
• Expertise in data design and building scalable data architectures.