Senior Fraud Modeling Engineer

SoFi; Frisco (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

SoFi is seeking a Fraud Model Developer to join the Fraud Model Development team in Frisco, TX. You will build, evaluate, and monitor machine learning models that support fraud decisions across SoFi’s lending and financial products.

The role requires strong ML, statistical modeling, and data analysis skills, with collaboration across Risk, Product, Engineering, and Finance. Expect ongoing model governance and production deployment work.

Qualifications

• 5+ years in fraud modeling or related quantitative field.
• Master's or Doctoral degree in a quantitative field or equivalent experience.
• Advanced Python and SQL for data analysis and ML development.
• Experience building dashboards with Tableau or similar tools.
• Proven track record in ML model development and evaluation.
• Experience monitoring model performance and handling data drift.

Responsibilities

• Develop fraud models to reduce losses and false positives.
• Aggregate and clean large datasets across environments.
• Analyze patterns and drivers of losses across products.
• Design, test, validate, and recalibrate models using ML methods.
• Monitor performance and detect model degradation.
• Forecast losses and conduct scenario analyses.
• Automate model monitoring, reporting, and dashboards.
• Collaborate with engineers and business teams to deploy models.
• Translate results into actionable business recommendations.
• Maintain model governance and documentation.

Skills

Fraud modeling

Loss forecasting

Machine learning

Python

SQL

Data analysis

Tableau

Education

Master's or PhD in Statistics/Math/Economics/Engineering/CS

Tools

Tableau

Job description

SoFi is seeking a Fraud Model Developer to join the Fraud Model Development team in Frisco, TX. You will build, evaluate, and monitor machine learning models that support fraud decisions across SoFi’s lending and financial products.

The role requires strong ML, statistical modeling, and data analysis skills, with collaboration across Risk, Product, Engineering, and Finance. Expect ongoing model governance and production deployment work.