Senior Data Modeler, Fraud Risk Detection

Role Overview:

• Work with senior data scientists to translate fraud questions into testable hypotheses.
• Help build machine learning models for fraud detection across account opening and identity risk.
• Partner with the score monitoring team to support model and feature monitoring.

Qualifications:

• 1+ years in data science or related quantitative field with a degree in computer science, statistics, or engineering.
• Foundation in supervised learning, model evaluation, and feature selection.
• Proficiency in Python and tools like pandas, NumPy, and scikit-learn.

What You'll Do:

• Explore complex datasets to identify fraud patterns and behavioral signals.
• Evaluate models using technical and business metrics like precision and recall.
• Help prepare analyses and communicate findings to both technical and nontechnical audiences.

Benefits:

• Great compensation package and bonus plan.
• Core benefits including medical, dental, vision, and matching 401K.
• Flexible time off including volunteer time off, vacation, sick, and 12-paid holidays.