As a Staff Data Scientist, you will be a key strategic partner to the Growth (Product and Engineering), Marketing, Sales, and Finance & Strategy teams, developing both intelligent data products and insights, and creating end-to-end systems and measurement plans for accelerating Stripe's overall growth engine.

Responsibilities:

• Provide direction to cross-functional partners on business strategy for enabling Stripe's growth, leveraging your expertise in causal inference / experimentation, modeling, analytical insights, and data foundations.
• Provide senior technical direction to data teams on horizontal technical areas, including experimentation, attribution, forecasting, observability, etc.; assume hands-on leadership, especially when helping teams resolve complex problems through iterative execution.
• Identify broad company problems and opportunities that can be tackled through data science; work with relevant teams to design and build the data science outputs that deliver outsized value to our users and our business.
• Contribute to the overall strategy, roadmap, and vision of your data science team and organization.
• Evangelize and inspire best practices across data science; lead by example to build a culture of craftsmanship and innovation.
• Provide mentorship to our data science talent to help them grow technically and professionally.

Minimum requirements:

• 10+ years of data science experience OR equivalent combined industry and research experience in a quantitative field.
• B.S. / M.S. / Ph.D. in a quantitative field (e.g. Statistics, Mathematics, Economics, Operations Research, Quantitative Marketing, Physical Sciences, Engineering, etc.).
• Experience with modern causal inference techniques.
• Demonstrated experience of leading organization-wide initiatives spanning multiple teams, or leveraging deep domain expertise to influence tech roadmap planning and execution.
• Demonstrated ability to effectively collaborate across multiple teams and stakeholders to drive business outcomes.
• Experience creating alignment with stakeholders in ambiguous and complex situations.
• Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design.
• Experience, mentoring, and investing in the development of peers.

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