Stripe is hiring a Staff Data Analyst in 7112 Data Science — US. The overview below is synthesized from the employer posting on stripe.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
Who we are
About Stripe
Company context from the listing:
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.
About the team
Company context from the listing:
The Risk Data Science team builds the data foundations, models, and measurement frameworks that power Stripe's risk and product decisions — from underwriting and reserves to merchant interventions and enablements. We're at an inflection point: as Stripe increasingly offers risk capabilities as a product to platforms and users, we need a data leader to shape how we build, measure, and evolve our risk data strategy across the
What you’ll do
Day-to-day scope for the Staff Data Analyst as described in the posting:
The listing frames the Staff Data Analyst at Stripe as a hands-on product role. Define the metrics, data products, and analytical frameworks needed as Stripe brings risk capabilities to platforms and connected accounts at scale. Partner with Product, Engineering, and Risk leadership to ensure data investments align with the product roadmap. You will design metrics, pipelines, and data products that serve as the analytical backbone for risk decisioning.
You will own the definition, reliability, and visibility of our most important risk metrics. Establish a canonical set of north star and operational metrics and ensure they are trustworthy, well-documented, and consistently surfaced to the right audiences.
You will also own and evolve Stripe's risk experimentation strategy by defining what we test, how we measure, and how we learn. Ensure we can rigorously evaluate the impact of changes to risk policies, merchant journeys, and risk models across diverse merchant populations.
Finally, you will mentor and raise the bar for the Data Analysts on the team. Set technical and strategic standards.
Who you are
Experience and skills the team lists as required:
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.
Minimum requirements
Experience and skills the team lists as required:
- 10+ years in Data Analytics, Data Science, or related roles
- Track record of defining and driving data strategy across multiple teams — not just executing on a roadmap, but shaping it
- Experience designing experimentation frameworks or measurement strategies for complex, multi-variant systems (e.g., risk policies, pricing, marketplace dynamics)
- Deep expertise in SQL; proficiency in Python
- Strong ability to translate ambiguous business problems into structured analytical approaches and communicate findings to executive stakeholders
- Experience building and scaling data products (metrics frameworks, pipelines, dashboards) that become operational infrastructure, not one-off analyses
- Demonstrated ability to influence without authority across engineering, product, and business teams
- Proficiency with AI tools to accelerate model development, analysis and coding
Preferred qualifications
Experience and skills the team lists as required:
- Master’s degree in Mathematics, Statistics, Economics, Engineering, or a related technical field
- Experience in risk, trust & safety, or related domains and understanding of risk in the Fintech space
- Experience building data for platform/product offerings where data is part of the product surface, not just internal analytics
- Familiarity with causal inference and A/B testing in non-standard environments (e.g., where randomization is constrained by risk considerations)