Machine Learning Engineer Fraud | Fintech Payments

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

Now Hiring: Machine Learning Engineer - Fraud | Fintech / Payments

• Location: Chicago, IL (Onsite/Hybrid)
• Compensation: $225K-$275K Base + Bonus & Equity
• Industry: MUST HAVE Fintech | Payments Infrastructure | Fraud Prevention

I'm partnering with a rapidly growing fintech company seeking a Machine Learning Engineer / ML Lead to build and own its fraud detection and risk decisioning systems.

Key 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.

Technical Requirements:

• 5+ years in Machine Learning, Applied Data Science, or Production ML.
• Strong experience with Machine Learning, Statistical Modeling, Feature Engineering, MLOps, and Cloud Infrastructure.
• Experience building production fraud-detection and real-time risk-scoring systems.
• Background in payments, payment processing, acquiring, PSPs, or PayFacs.
• Experience with model monitoring, data pipelines, and large-scale transaction data.

Preferred:

Experience building ML functions from the ground up, real-time scoring, and fraud/chargeback systems.

Sorry, no C2C or sponsorship.

#Hiring #MachineLearning #FintechJobs #FraudDetection #ChicagoJobs #MLOps #Payments #ArtificialIntelligence