Senior Fraud Modeling Engineer (ML & Risk)

United States Digital Space LLC; Frisco (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

United States Digital Space LLC is seeking a Fraud Model Developer to build, evaluate, and monitor ML models that support data-driven fraud decisions across Personal Loans, Credit Cards, and more.

You will develop quantitative solutions to reduce fraud losses, minimize false positives, and cut operational costs, while collaborating with risk, product, and engineering teams to ensure scalable deployment and clear result communication.

Qualifications

• Five or more years of experience in fraud modeling or related field.
• Master's or PhD in Statistics, Mathematics, Economics, Engineering, CS, or equivalent experience.
• Advanced proficiency in Python and SQL for data analysis and model development.
• Experience creating analytical reports or dashboards using Tableau or similar tools.
• Experience developing and evaluating statistical and ML models (regression, trees, GBM, RF, NN).
• Hands-on knowledge of fraud-loss forecasting and risk-modeling techniques.
• Experience monitoring model performance and recalibrating models for data drift.
• Ability to translate model results into measurable business outcomes.
• Strong cross-functional collaboration skills in fast-paced environments.
• Proactive problem solver focused on results.

Responsibilities

• Develop quantitative, statistical, and ML models to reduce fraud losses and false positives.
• Aggregate, clean, and synthesize large datasets from multiple environments for model work.
• Analyze complex data to identify fraud patterns and product performance drivers.
• Design, test, validate, and recalibrate fraud models using robust methods.
• Monitor model performance and detect degradation or data drift.
• Forecast fraud losses and run scenario analyses to assess business impact.
• Automate recurring model monitoring, reporting, and dashboards.
• Investigate external risk data and industry trends for opportunities.
• Collaborate with Engineering and ML platform teams for deployment.
• Communicate findings to business and risk partners to influence decisions.
• Maintain model documentation and governance processes.

Skills

Fraud modeling

Loss forecasting

Machine learning

Python

SQL

Data analysis

Model evaluation

Education

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

Tools

Tableau

AWS

Python

Job description

United States Digital Space LLC is seeking a Fraud Model Developer to build, evaluate, and monitor ML models that support data-driven fraud decisions across Personal Loans, Credit Cards, and more.

You will develop quantitative solutions to reduce fraud losses, minimize false positives, and cut operational costs, while collaborating with risk, product, and engineering teams to ensure scalable deployment and clear result communication.