Associate Data Scientist

The role

You will build and maintain features and components for graph-native models to detect fraud, collusion, and identity risk. You will support the design, training, and evaluation of statistical, AI/ML, and deep learning models under senior guidance.

What you will do

• Build and maintain features and components for graph-native models used to detect fraud, collusion, and identity risk
• Support the design, training, and evaluation of statistical, AI/ML, and deep learning models for fraud and risk
• Run experiments, clean and prepare data, and do light pipeline work to help tune model performance
• Write production-quality code backed by statistics and ML
• Help build out ML observability for the models you work on
• Document your work clearly

Required qualifications

• BS/MS in ML, CS, Math, Stats, or a related field
• 1 to 3 years in DS/AI/ML Engineering roles (internships with real shipped work count)
• Strong Python
• Working knowledge of SQL
• Some experience taking a model from a notebook toward something production-adjacent
• Comfort with ambiguity and unlabelled data
• Initiative to ask questions and look things up

Nice to have

• Exposure to a cloud platform (AWS/Databricks/Azure)
• Experience with fraud, risk, payments, or compliance data
• Prior exposure to graph-based thinking (even coursework or personal projects)

Benefits

• Health benefits
• Flexible PTO
• Learning budget

About the company

Bureau is a unified risk decisioning platform for Compliance, Fraud, and Transaction risks. Its platform is a single decision-making engine powered by a 1 billion+ identity knowledge graph.