Fraud & Risk ML Lead — Production Models at Scale

Merraine Group; Chicago (IL); On-site; USD 225,000 - 275,000; Full time

Benefits offered by this job

Equity participation

Health and wellness benefits

401(k) retirement savings plan

Job summary

Merraine Group is seeking a Machine Learning Lead to build and advance fraud and risk intelligence at the core of its payments platform. The role combines strategy with hands-on development of production-grade models to improve approvals, reduce fraud, and strengthen merchant risk management.

The ideal candidate will lead ML development, partner with Engineering, Product, Operations, and Risk, and shape the long-term roadmap for fraud prevention and intelligent payment optimization.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related field; advanced degree preferred.
• Five or more years of experience in machine learning, applied data science, or production ML environments.
• Direct experience building fraud and risk models within payments or fintech environments.
• Demonstrated success deploying ML models into production and managing the full lifecycle.
• Strong ML methodologies, statistics, feature engineering, and analysis of high-volume transaction data.

Responsibilities

• Design, develop, and deploy ML models to strengthen fraud detection and risk decisioning.
• Engineer and evaluate features using transaction, behavioral, and external data.
• Improve model performance through experimentation, monitoring, retraining, and optimization.
• Identify emerging fraud patterns and create scalable mitigation approaches.

Skills

Machine Learning

Fraud Detection

Risk Modeling

Data Analysis

Payments Industry Knowledge

Education

Bachelor's degree in Computer Science or related

Advanced degree preferred

Tools

MLOps

Cloud Platforms

Job description

Merraine Group is seeking a Machine Learning Lead to build and advance fraud and risk intelligence at the core of its payments platform. The role combines strategy with hands-on development of production-grade models to improve approvals, reduce fraud, and strengthen merchant risk management.

The ideal candidate will lead ML development, partner with Engineering, Product, Operations, and Risk, and shape the long-term roadmap for fraud prevention and intelligent payment optimization.