Who we are
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, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
About the team
The Risk Interventions Data Science Team aims to ensure we achieve the right balance between mitigating risk and enabling our customers to achieve their business objectives. Working cross-functionally with various teams within the organization, the team is focused on developing models, methods, and frameworks for ensuring efficient compliance with regulatory requirements, appropriately targeted interventions and a low friction user experience.
What you’ll do
Responsibilities
- Identify broad company problems and opportunities that can be tackled through data science; develop evidence of the validity and utility of data science solutions (e.g. through prototypes or MVP); work with relevant teams to design and build the data science components that deliver outsized value to our users and our business.
- Provide senior technical direction to teams and inspire a larger community across Stripe that are working in the data science space; assume hands-on leadership, especially when helping teams set their long-term vision and resolve complex problems through iterative execution.
- Join the Risk Interventions DS leadership team, contributing to overall strategy, roadmap, and vision.
- 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.
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- 10 years of Data Science experience OR equivalent combined work and academic experience in a quantitative field.
- 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
- Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design.
- Experience, mentoring, and investing in the development of scientists, engineers, and peers
Preferred qualifications
- Experience in the development and implementation of machine learning, statistical or forecasting frameworks
- Experience with data modeling and the deployment of ETL pipelines
- Experience with experimental design and analysis
- Experience in building data products focused on risk and financial systems
- Experience thinking about user experience, marketplace dynamics and complex systems
- Experience with creating alignment with stakeholders in ambiguous and complex situations.
- Experience developing and deploying metric frameworks