Senior Machine Learning Data Scientist (Fraud Detection)

TL;DR

Senior Machine Learning Data Scientist (Fraud Detection): Developing and deploying production-grade machine learning models to detect fraud and assess risk for a post-purchase protection platform with an accent on feature engineering and model lifecycle management. Focus on translating complex fraud patterns into scalable ML solutions and monitoring model performance in production.

Location: Remote (Must be located within the continental United States)

Salary: $135,000 - $165,000 per year

Company

AI-driven platform enhancing the post-purchase experience for retailers through automated fulfillment and advanced fraud detection.

What you will do

• Own the full ML model lifecycle from requirements and experimentation to evaluation and production deployment.
• Translate complex fraud patterns into scalable ML solutions and define success metrics.
• Design and maintain feature engineering pipelines for model development.
• Monitor production model quality, detect data drift, and manage retraining cycles.
• Collaborate with Product, Engineering, and Fraud Intelligence teams to execute risk strategies.

Requirements

• Bachelor's degree or higher in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering.
• 3+ years of experience building and deploying machine learning systems into production.
• Strong proficiency in Python and SQL.
• Hands-on experience with PyTorch, scikit-learn, and XGBoost.
• Must be based in the continental United States.

Nice to have

• Experience building fraud detection or risk assessment systems.
• Proficiency with AWS SageMaker.
• Experience with graph data and PyTorch Geometric.
• Experience with model observability tools like Arize.

Culture & Benefits

• Competitive salary and stock options in a fast-growing early-stage startup.
• Full medical, dental, and vision insurance.
• Generous and flexible paid time off policy.
• 401(k) retirement plan with financial guidance from Morgan Stanley.
• Collaborative and supportive environment with a diverse team.