Description
We're looking for a Data Science Manager to join our team at Stripe. As a Data Science Manager, you will be responsible for the success of your team, driving the roadmap and priorities, collaborating with stakeholders, and managing a high-performing team of data scientists.
The MaaS Data Science team is central to all money movements, embedded finance, and platform solutions for our biggest and most complex customers. The two roles available are in Embedded Finance (Capital, Issuing) and Connect (Stripe's solution and growth suite for platforms and marketplaces).
The Growth Data Science team helps businesses on Stripe get started both quickly and effectively. We work closely with Growth product and engineering leads to optimize every step of the user journey, from awareness and acquisition, through product adoption, to usage growth and retention.
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:
- 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, 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 verbally.
- Thrive on a high level of autonomy and responsibility.
- Foster a healthy, inclusive, challenging, and supportive work environment.
Preferred 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.