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StripeStripeSeattle, WA

Data Science Manager, Growth

Lead and manage a team of data scientists focused on finance and strategy initiatives. Drive roadmap, mentor team members, and partner cross-functionally to deliver scalable ML systems and data products.

Salary not listed
Hybrid10+ YOEEngineering Management

About the role

Responsibilities

  • 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.

Requirements

  • 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, and have hands-on experience with challenging problems.
  • Work very well cross-functionally, and are able to think rigorously and make hard decisions and tradeoffs.
  • Clear and persuasive communication skills in writing and in speech.
  • Thrive on a high level of autonomy and responsibility.
  • Foster a healthy, inclusive, challenging, and supportive work environment.

Nice-to-Haves

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

Skills

Machine LearningData ScienceMetrics DesignPredictive ModelingTime Series ForecastingOptimizationData ArchitectureCross-Functional CollaborationTeam LeadershipStakeholder Management
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