Staff Data Scientist, Security

Stripe · n/a · 7112 Data Science · listed July 6, 2026

The shape of it

Seniority
Staff
Experience asked
10+ years
Where
Not stated
Requirements listed
8
Length
551 words

In the posting’s own words

You’ll be joining the data science team at Stripe responsible for our overall infrastructure, with a special focus on Stripe’s security. Projects include, but are not limited to:

What it asks for · 8

  • 10+ years of data science experience or equivalent combined industry and research experience in a quantitative field.
  • Bachelor’s, Master’s, or Ph.D. in a quantitative field (e.g. Statistics, Mathematics, Economics, Operations Research, Quantitative Marketing, Physical Sciences, Engineering, etc.).
  • 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, and leading company-level initiatives.
  • Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design.
  • Proficiency with AI tools to accelerate model development, analysis, and coding.
  • Experience mentoring and investing in the development of peers.

Also a plus

  • Strong preference for experience working with security or security-adjacent teams, and familiarity with contemporary security tools and practices.
  • Experience in the end-to-end development and production implementation of machine learning, statistical, or forecasting frameworks (beyond building model prototypes).
  • Experience developing and deploying metrics and observability frameworks.

What the job covers

  • Provide senior technical direction to data teams on horizontal technical areas, including detection, modeling, metrics, 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 quantitative outputs and artifacts that deliver outsized value to our users and our business.
  • Provide data-driven guidance to cross-functional partners on strategy for tracking and protecting Stripe assets from external and internal threats.
  • 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.

Degree language

  • Bachelor’s, Master’s, or Ph.D. in a quantitative field (e.g. Statistics, Mathematics, Economics, Operations Research, Quantitative Marketing, Physical Sciences, Engineering, etc.).

Tools and skills named

Security & compliance
  • Security7×
Ways of working
  • Mentorship2×
  • Cross-functional
Cloud & infra
  • Observability2×
Product & design
  • Roadmap2×
Data
  • Statistics
Go to market
  • Forecasting
Models & research
  • Machine learning

Words the posting leans on

  • data11×
  • experience8×
  • data science6×
  • security5×
  • quantitative4×
  • requirements4×
  • assets3×
  • business3×
  • demonstrated3×
  • design3×
  • development3×
  • execution3×
  • model3×
  • provide3×
  • research3×
  • strategy3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched August 24, 2026 and last changed by Stripe on August 18, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.