Data Science Manager

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet.

About the Teams

MaaS (Money as a Service) Data Science

The MaaS Data Science team is central to all money movements, embedded finance, and platform solutions for our biggest and most complex customers. The team works on Embedded Finance (Capital, Issuing) and Connect (Stripe's solution and growth suite for platforms and marketplaces). We set the data foundations for company-wide data primitives and external products, drive strategy through modeling, analytics, and experimentation, build world-class data-driven and ML-powered product experiences, and partner closely with cross-functional teams across Product, Engineering, Risk, Marketing, Operations, and Strategy.

Growth Data Science

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. The team is known for being an experimentation powerhouse, for pushing the frontiers of causal analysis and cumulative impact measurement, and for developing a deep understanding of the user journey that drives the product roadmap.

What You'll Do

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 maintain a strong user focus.

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 succeed
• Work with data scientists, analysts and engineers on creating technical solutions and communicating effectively across teams and senior leadership