# Staff Data Analyst

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Remote
**Role:** Data Analytics
**Experience:** 10+ years
**Skills:** SQL, Python, Data Pipelines, Metrics Frameworks, Dashboards, A/B Testing, Causal Inference, Experimentation Frameworks, Data Strategy
**Posted:** 2026-05-13

> Staff Data Analyst drives risk data strategy at Stripe, defining metrics, pipelines, and experimentation frameworks while partnering cross-functionally. Requires 10+ years experience, SQL/Python expertise, and mentoring skills.

## Job Description

## Responsibilities

- Drive data strategy for risk as a product offering, defining metrics, data products, and analytical frameworks.
- Partner with Product, Engineering, and Risk leadership to align data investments with product roadmap.
- Design metrics, pipelines, and data products for risk decisioning.
- Own definition, reliability, and visibility of key risk metrics, including north star and operational metrics.
- Build and maintain infrastructure for metric accuracy, with ownership, alerting, and scalable pipelines.
- Own and evolve risk experimentation strategy, defining tests, measurements, and learning from changes to policies, journeys, and models.
- Mentor data analysts, setting technical and strategic standards, guiding on problem framing, analysis structure, and stakeholder communication.

## Minimum Requirements

- 10+ years in Data Analytics, Data Science, or related roles.
- Track record of defining and driving data strategy across multiple teams.
- Experience designing experimentation frameworks or measurement strategies for complex 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 to executives.
- Experience building and scaling data products (metrics frameworks, pipelines, dashboards) as operational infrastructure.
- Demonstrated ability to influence without authority across engineering, product, and business teams.

## Preferred Qualifications

- Master’s degree in Mathematics, Statistics, Economics, Engineering, or related technical field.
- Experience in risk, trust & safety, or Fintech risk domains.
- Experience building data for platform/product offerings where data is part of the product.
- Familiarity with causal inference and A/B testing in non-standard environments.

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