Staff Data Scientist - Risk ML
San Francisco, CA, New York, NY, Portland, OR, Remote$239k - $298.8kfull-timePosted 1mo ago
About the role
Machine Learning-focused Data Scientist to support Mercury's Risk team, building and deploying fraud-detection models, ensuring data quality, and leading best practice adoption in a fast-paced fintech environment.
Responsibilities
- Build, validate, and deploy machine learning models to identify and prevent fraud in real time
- Support the reproducibility and robustness of said models through documentation, testing, and monitoring
- Ensure data quality and reliability across pipelines and tools
- Collaborate with Risk Strategy to ideate on model inputs and applications and with Engineering optimize deployment and observability
- Act as a technical lead prototyping, iterating on, and codifying best practices - and bringing the rest of the team along
Qualifications
- 7+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 5+ years of ML experience
- Proficiency in SQL and experience using it to understand and manage imperfect data
- Proficiency in Python and experience with statistical modeling and machine learning
- Experience deploying and monitoring machine learning models in production
- Comfort working in a fast-paced environment with evolving priorities
- Demonstrated ability to lead and empower others, delivering not just on your own work, but upleveling those around you
- The ability to drive strategic alignment between teams with differing roadmaps, timelines, or architectures
Skills
Required:SQLPythonMachine learning / statistical modelingProduction ML deploymentLeadership / mentoring
Last updated Sep 23, 2026. Interested? Apply on the company site.
About Mercury
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