Mercury
Senior Data Scientist - Risk ML
$167K–$251K
San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States +1 · Remote · Senior · Full-time · Posted Sep 2, 2026
- Location
- San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Any Office or Remote - Experience
- 5+ years working with and analyzing large datasets, including 3+ years of ML experience; ideally 1+ years of relevant risk experience.
About the job
Build and operate machine learning systems that detect and prevent fraud and support risk monitoring at Mercury.
What you'll do
- Build, validate, and deploy real-time fraud detection models; document, test, and monitor them for robustness and reproducibility.
- Ensure data quality and reliability across pipelines and tools.
- Collaborate with Risk Strategy and Engineering on model inputs, applications, deployment, and observability.
What they ask for
- 5+ years working with and analyzing large datasets to solve problems and drive impact, including 3+ 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.
Nice to have
- 1+ years of relevant risk experience.
- Familiarity with LLMs or other GenAI and their application to risk or fraud detection; modern data tools such as dbt; model governance in regulated industries; or building zero-to-one solutions in ambiguous or greenfield spaces.
Pay
$166,600 — $250,900 USD (base salary); $157,400 — $237,100 CAD (base salary)
Tools
SQL, Python, LLMs, GenAI, dbt
AI focus
Build and deploy machine learning models for real-time fraud detection and prevention; familiarity with LLMs or other GenAI for risk or fraud detection is a nice-to-have.
Model-written summary · the original posting is authoritative