[Hiring] Data Science Manager @Stripe

Role Description

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 have a deep understanding of how to drive efficient data science teams and you’ll have a strong user-focus. You’ll be working with data scientists, analysts and engineers on creating technical solutions and communicating effectively across teams and senior leadership.

• 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.

Qualifications

• A PhD or 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.
• Managed teams that have built and shipped machine learning systems and data products at scale, with hands-on experience with challenging problems.
• Ability to work very well cross-functionally, think rigorously, and make hard decisions and tradeoffs.
• Clear and persuasive communication skills in writing and verbally.
• Thrive on a high level of autonomy and responsibility.
• Foster a healthy, inclusive, challenging, and supportive work environment.

Requirements

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