Senior ML Data Scientist — Fraud Risk

Mercury; San Francisco (CA); On-site; USD 239,000 - 299,000; Full time

Job summary

Mercury is hiring a Machine Learning-focused Data Scientist to join the Risk team in San Francisco. You will build, validate, and deploy real-time fraud-detection models, ensure data quality across pipelines, and collaborate with Risk Strategy and Engineering to optimize deployment and observability.

You will also lead by example, codify best practices, and uplift peers. The role emphasizes data-driven decisions in a fast-moving fintech environment, with a focus on governance, monitoring, and

Qualifications

• 7+ years of experience 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

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

Skills

SQL

Python

Large datasets

ML experience

Production deployment

Leadership

Strategic alignment

Tools

dbt

Job description

Mercury is hiring a Machine Learning-focused Data Scientist to join the Risk team in San Francisco. You will build, validate, and deploy real-time fraud-detection models, ensure data quality across pipelines, and collaborate with Risk Strategy and Engineering to optimize deployment and observability.

You will also lead by example, codify best practices, and uplift peers. The role emphasizes data-driven decisions in a fast-moving fintech environment, with a focus on governance, monitoring, and