Senior ML Fraud Risk Scientist — Real-Time Production Models

Mercury; United States; On-site; USD 167,000 - 251,000; Full time

Job summary

Mercury in the United States is seeking a Machine Learning-focused Data Scientist to support our Risk team, developing real-time fraud detection models and strengthening data quality across pipelines. You’ll work with product, engineering, and risk to deploy robust ML systems, monitor performance in production, and ensure reproducibility through thorough documentation and testing.

This role offers exposure to fintech-scale data and the chance to influence risk strategy while helping Mercury

Qualifications

• 5+ years of experience analyzing large datasets with 3+ years of ML experience.
• Proficiency in SQL to understand and manage imperfect data.
• Proficiency in Python with experience in statistical modeling and ML.
• Experience deploying and monitoring ML models in production.
• Comfort working in a fast-paced environment with evolving priorities.

Responsibilities

• Build, validate, and deploy ML models to detect fraud in real time.
• Support reproducibility and robustness via documentation, testing, and monitoring.
• Ensure data quality and reliability across data pipelines and tools.
• Collaborate with Risk Strategy and Engineering to optimize deployment and observability.

Skills

ML experience

SQL proficiency

Python

Model deployment

Data analysis

Job description

Mercury in the United States is seeking a Machine Learning-focused Data Scientist to support our Risk team, developing real-time fraud detection models and strengthening data quality across pipelines. You’ll work with product, engineering, and risk to deploy robust ML systems, monitor performance in production, and ensure reproducibility through thorough documentation and testing.

This role offers exposure to fintech-scale data and the chance to influence risk strategy while helping Mercury