Fraud ML Engineer: Real-Time Risk for Payments (Hybrid)

Access Search, Inc.; Chicago (IL); Hybrid; USD 225,000 - 275,000; Full time

Job summary

Access Search, Inc. is partnering with a rapidly growing fintech company to hire a Machine Learning Engineer / ML Lead who will own fraud detection and risk decisioning systems in Chicago.

The role requires 5+ years in ML, strong expertise in ML, statistical modeling, feature engineering, MLOps, and cloud infrastructure, with experience building production fraud-detection and real-time risk-scoring systems.

Qualifications

• 5+ years in Machine Learning, Applied Data Science, or Production ML.
• Strong experience with ML, Statistical Modeling, Feature Engineering, MLOps, and Cloud Infrastructure.
• Experience building production fraud-detection and real-time risk-scoring systems.

Responsibilities

• Develop and deploy real-time ML models for fraud detection, payment authorization, and merchant risk.
• Build scalable ML pipelines, feature engineering processes, and MLOps infrastructure.
• Improve fraud detection, approval rates, and chargeback prevention.
• Lead ML initiatives from development through production deployment.

Skills

Machine Learning

Statistical Modeling

Feature Engineering

MLOps

Cloud Infrastructure

Fraud Detection

Job description

Access Search, Inc. is partnering with a rapidly growing fintech company to hire a Machine Learning Engineer / ML Lead who will own fraud detection and risk decisioning systems in Chicago.

The role requires 5+ years in ML, strong expertise in ML, statistical modeling, feature engineering, MLOps, and cloud infrastructure, with experience building production fraud-detection and real-time risk-scoring systems.