Remote Data Science Manager

Summary

Join Stripe's Developer Experience and Platform Product (DEeP) Data Science team as a Data Science Manager. You'll drive the roadmap and priorities for your team, collaborate with stakeholders across the organization, lead and manage processes to help the team do its best work, and contribute to broad data science initiatives.

Requirements

• You have at least 3 years of direct management experience leading data science and ML teams, and 10 years of overall data science experience
• You have 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 verbally
• You thrive on a high level of autonomy and responsibility
• You foster a healthy, inclusive, challenging, and supportive work environment

Responsibilities

• Drive the roadmap and priorities for your team
• 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

Preferred Qualifications

• A PhD or MS in a quantitative field (e.g., Statistics, Operations Research, Economics, Computer Science, Engineering)
• You are comfortable working with geographically distributed teams
• Expertise in time series forecasting, predictive modeling, or optimization
• Expertise in data design and building scalable data architectures