Senior Remote ML Scientist - Fraud & Risk in Production

North American Search Group; United States; Remote; USD 135,000 - 165,000; Full time

Job summary

North American Search Group is seeking a Senior Machine Learning Data Scientist (remote) to design, build, and sustain production-grade ML models aimed at fraud detection and revenue growth. You will manage the full lifecycle from experimentation to deployment, collaborating with ML Engineers and cross-functional teams.

The role requires 3+ years building ML systems in production and a quantitative degree. Strong Python/SQL skills and experience with PyTorch, scikit-learn, and XGBoost are

Qualifications

• 3+ years of experience building and deploying ML systems into production.
• Bachelor’s degree or higher in a quantitative discipline such as Math, Stats, CS, Engineering, or Physics.

Responsibilities

• Build, evaluate, and scale production-grade ML models using transactional signals from hundreds of millions of users to combat fraud, evaluate risk, and boost revenue.
• End-to-End Model Lifecycle: Lead model experimentation, design, testing, and evaluation, partnering with ML Engineers to deploy models into production infrastructure.
• Fraud & Risk Framing: Translate complex fraud behaviors into structured machine learning solutions, knowing when to deploy ML versus simpler analytical approaches.
• Feature Engineering & Pipelines: Design and maintain robust feature pipelines to support model development and real-time evaluation.
• Production Observability: Monitor production model performance, track data drift over time, and determine retraining schedules.
• Cross-Functional Strategy: Collaborate with Product, Engineering, Fraud Operations, and GTM teams to align machine learning solutions with business objectives.

Skills

Python

SQL

Education

Bachelor’s degree or higher in a quantitative discipline

Tools

PyTorch

scikit-learn

XGBoost

Job description

North American Search Group is seeking a Senior Machine Learning Data Scientist (remote) to design, build, and sustain production-grade ML models aimed at fraud detection and revenue growth. You will manage the full lifecycle from experimentation to deployment, collaborating with ML Engineers and cross-functional teams.

The role requires 3+ years building ML systems in production and a quantitative degree. Strong Python/SQL skills and experience with PyTorch, scikit-learn, and XGBoost are