Staff Data Analyst

Stripe

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Toronto, CanadaAtlanta, GAChicago, IL
Salary
$179,000–$268,400 / yr
Posted
143 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $179k
This role $224k
$124k most similar roles pay here $284k

This role pays more than 78% of similar roles. Most pay $139,914–$218,250 — the shaded band above. At the midpoint, this role pays about $224k versus about $179k for comparable roles.

Based on 240 similar postings.

Employer

About Stripe

Stripe is a financial infrastructure platform for internet businesses, providing payment processing, billing, fraud prevention, and banking-as-a-service APIs to businesses of all sizes globally. Industry: Payments Infrastructure & Financial Technology

Stripe currently has 99 open roles on FindRole.

Listed pay typically runs $203,600–$288,000 across 96 roles with salary data.

Most-posted roles

View all roles at Stripe

At a glance

TL;DR · Staff Data Analyst

Role Posting Log in to save

As a Staff Data Analyst on the Risk Data Science team, you will drive the data strategy for risk as a product offering. You will define metrics, data products, and analytical frameworks to support underwriting, reserves, and merchant interventions while partnering with Product, Engineering, and Risk leadership. Your daily work involves owning the reliability of core risk metrics, building scalable pipelines, and evolving experimentation strategies to evaluate changes in risk policies and models. You will also mentor team members by setting technical standards and framing ambiguous problems for executive stakeholders. The role requires deep expertise in SQL, proficiency in Python, and experience with AI tools. You must be able to design measurement frameworks for complex systems like pricing or marketplace dynamics while building operational infrastructure rather than one-off analyses within the fintech risk domain.

What does a Data Analyst earn?

Median $127875 from 54 postings across 18 companies.

See salary data

Skills

SQL Python Data Analytics Data Science A/B Testing Causal Inference Metrics Frameworks Dashboards AI Tools

What you'll do

  • Define metrics, data products, and analytical frameworks for risk capabilities offered to platforms and users.
  • Design the pipelines and infrastructure that serve as the analytical backbone for risk decisioning.
  • Establish a canonical set of trustworthy, well-documented north star and operational risk metrics.
  • Maintain automated systems to ensure metric reliability and alert on regressions in the data landscape.
  • Develop and evolve the risk experimentation strategy to evaluate impacts of policy changes and models.
  • Translate ambiguous business problems into structured analytical approaches for executive stakeholders.
  • Build scalable data products that function as operational infrastructure rather than one-off analyses.
  • Mentor team members by setting technical standards and guiding them through complex problem framing.

What we're looking for

  • 10+ years of experience in Data Analytics, Data Science, or related roles.
  • Track record of defining and driving data strategy across multiple teams to shape the roadmap.
  • Experience designing experimentation frameworks or measurement strategies for complex, multi-variant systems.
  • Deep expertise in SQL and proficiency in Python.
  • Ability to translate ambiguous business problems into structured analytical approaches for executive stakeholders.
  • Experience building and scaling data products like metrics frameworks, pipelines, and dashboards as operational infrastructure.
  • Demonstrated ability to influence without authority across engineering, product, and business teams.
  • Proficiency with AI tools to accelerate model development, analysis, and coding.
  • Master’s degree in Mathematics, Statistics, Economics, Engineering, or a related technical field (preferred).
  • Experience in risk, trust & safety, or the Fintech space (preferred).
  • Experience building data for platform/product offerings where data is part of the product surface (preferred).
  • Familiarity with causal inference and A/B testing in non-standard environments (preferred).

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