Senior Machine Learning Data Scientist (Fraud)

TL;DR

Senior Machine Learning Data Scientist (Fraud): Developing and optimizing ML models to detect and prevent fraud and assess risk for a post-purchase protection platform with an accent on the full data science lifecycle from feature engineering to production monitoring. Focus on translating complex fraud patterns into scalable ML systems and improving model quality using PyTorch and XGBoost.

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

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

Company

hirify.global provides AI-driven post-purchase solutions for retailers to enhance customer satisfaction and prevent fraud.

What you will do

• Own the full model lifecycle, including requirements, experimentation, development, evaluation, and model cards.
• Translate complex fraud patterns into scalable, production-grade ML solutions.
• Design and maintain feature engineering pipelines for model development.
• Monitor production model quality, tracking performance, detecting data drift, and managing retraining.
• Collaborate with leadership, fraud operations, product, and engineering teams to execute effective fraud strategies.
• Promote a culture of continuous learning and experimentation across data science teams.

Requirements

• Bachelor's degree or higher in a quantitative field (Mathematics, Statistics, Computer Science, Engineering, etc.).
• 3+ years of experience building and deploying machine learning systems into production.
• Strong proficiency in Python and SQL.
• Deep understanding of ML fundamentals, including model selection, evaluation methodology, and feature engineering.
• 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.
• Experience with AWS cloud ML platforms, specifically SageMaker.
• Knowledge of graph data and graph-based models (e.g., PyTorch Geometric).
• Experience with model monitoring and observability tools such as Arize.

Culture & Benefits

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