Staff Data Scientist, Stripe

• 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

Desirable

• You will be joining the part of Stripe’s data science organization that focuses on Growth and Go-to-Market efforts. Sample projects can include but are not limited to:
• Leveraging a wide variety of tools such as experimentation, forecasting, personalization, and algorithmic recommendations to enable businesses to accelerate their journey to accept payments on Stripe, and find additional Stripe financial products that they need to grow their business
• Delivering comprehensive ROI analysis for Stripe’s growth marketing spend through rigorous measurement methodologies (marketing mix models, multi-touch attribution, lifetime value, long-term holdouts, etc.)
• 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
• 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