October 17
• 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.
• 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. • 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.
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