Data Science Manager, Growth

About the Role

The Growth Data Science team is at the forefront of Stripe's efforts to optimize the user journey, from awareness and acquisition to product adoption and retention. As a leader in this team, you will have the opportunity to work on complex problems, develop innovative solutions, and drive business decisions with data. Your technical expertise and experience in designing metrics and guiding business decisions with data will be essential in this role.

The ideal candidate for this role will have a deep understanding of data science and its applications in the financial technology sector. You will be a strong leader, able to manage and motivate a team of data scientists, and a strategic thinker, able to drive business growth through data-driven decision making.

What You Will Do

• Drive the roadmap and priorities for your team, aligning with Stripe's overall business objectives
• Collaborate with stakeholders across the organization, including engineering, analytics, operations, finance, and marketing
• Lead and manage processes to help your 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
• Develop and maintain relationships with key stakeholders, including product and engineering leads
• Stay up-to-date with industry trends and advancements in data science, applying this knowledge to drive business growth

What We Are Looking For

• A PhD or MS or BS in a quantitative field, such as Statistics, Operations Research, Economics, Computer Science, or 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
• Experience managing teams that have built and shipped machine learning systems and data products at scale
• Hands-on experience with challenging problems, such as causal analysis and cumulative impact measurement
• Strong communication skills, both written and verbal, with the ability to think rigorously and make hard decisions and tradeoffs
• Ability to work effectively in a fast-paced, dynamic environment, with a high level of autonomy and responsibility
• Experience fostering a healthy, inclusive, challenging, and supportive work environment

Nice to Have

• Experience with Excel, SQL, and data visualization tools
• Knowledge of machine learning algorithms and techniques
• Experience working in a cloud-based environment, such as AWS or GCP
• Familiarity with agile development methodologies and version control systems, such as Git

Benefits and Perks

• Competitive salary and equity package
• Comprehensive health insurance, including medical, dental, and vision
• Flexible PTO and vacation policy
• Remote work stipend and home office setup support
• Professional development opportunities, including conference sponsorship and training programs
• Access to a network of experienced data scientists and engineers
• Opportunity to work on complex, high-impact problems that drive business growth
• Collaborative, dynamic work environment with a team of experienced professionals

• Tip: Showcase your technical expertise and experience in designing metrics and guiding business decisions with data, highlighting specific examples from your previous roles.
• Tip: Emphasize your leadership skills and experience managing high-performing teams, including your approach to coaching, mentoring, and talent development.
• Tip: Demonstrate your ability to work effectively in a fast-paced, dynamic environment, with a high level of autonomy and responsibility, and highlight your experience with agile development methodologies.
• Tip: Prepare to discuss your experience with machine learning algorithms and techniques, as well as your knowledge of data visualization tools and cloud-based environments.
• Tip: Research Stripe's company culture and values, and be prepared to discuss how your skills and experience align with these, and how you can contribute to the company's mission and goals.
• Tip: Be prepared to walk through your experience with data science projects, including your approach to problem-solving, data analysis, and communication of results.
• Tip: Highlight your ability to work effectively in a remote environment, including your experience with remote collaboration tools and your approach to staying connected with team members and stakeholders.