Staff Data Scientist, Security
Stripe · Not provided by source
MeritLog read this listing from Stripe's Greenhouse job board and last checked it on September 12, 2026.
Source: the employer's Greenhouse job board. Open the original listing for current details.
Job details
- Work model
- Not provided by source
- Salary
- Not listed by source
- Location
- n/a
- Occupation
- Data Scientists(O*NET 15-2051.00)
- Company website
- docs.google.com
Hiring context
How this role compares at Stripe
Stripe has 634 live roles in MeritLog’s catalog across 12 job families, and 103 of them are in data & analytics. 2 of those listings publish a pay range, a disclosure rate of 0%.
Stripe concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What you'd do
- 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.
What they're asking for
- Strong preference for experience working with security or security-adjacent teams, and familiarity with contemporary security tools and practices.SkillPreferred
- Experience in the end-to-end development and production implementation of machine learning, statistical, or forecasting frameworks (beyond building model prototypes).SkillPreferred
- Experience developing and deploying metrics and observability frameworks.SkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
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 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: • Leverage internal telemetry and logs to understand and design secure and safe access controls to sensitive data; • Develop methods to model, quantify, and ultimately de-risk security-related incidents on Stripe data, assets, and networks; • Collaborate across the company with engineering, PMs, and others to better understand, measure, and ultimately detect various malicious attack vectors. You will act as a key strategic data partner to the Security organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe keeps and maintains the highest level of safety and security for critical business assets and customer data. What you'll do Responsibilities • 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. 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 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. Preferred qualifications • 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.
Keep exploring