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Fraud Model Analyst

2 weeks, 2 days ago
United States
Full-time
Mid Level
Data Scientist
Data Science and Analytics
Machine Learning Python SQL
Apply Now
SoFi

SoFi

SoFi specializes in providing a comprehensive financial platform that empowers individuals to achieve their financial goals through services such as student loan refinancing, debt consolidation, home buying assistance, and investment opportunities, all...

Capital Markets
1K-5K
Founded 2011
$2900M raised
View All Jobs 66

Description

  • Manage the end-to-end lifecycle of vendor fraud models, including onboarding, documentation, monitoring, and periodic reviews.
  • Partner with Model Risk Management, Legal, and Compliance teams to ensure governance and regulatory adherence.
  • Coordinate with external vendors to obtain model documentation, technical details, and performance insights.
  • Analyze model performance metrics such as fraud capture, false positive rates, and drift to identify risks and improvement opportunities.
  • Investigate model behavior and data issues using SQL and internal datasets to support root cause analysis.
  • Support fraud model development efforts through feature analysis, performance benchmarking, and strategy design.
  • Collaborate with Fraud Strategy, Data Science, and Engineering teams to integrate vendor models into fraud decisioning frameworks.
  • Prepare and maintain model documentation, validation materials, and audit responses.
  • Support ongoing monitoring and reporting of vendor model performance, including degradation detection and recommended actions.
  • Act as a bridge between technical, fraud, and risk/compliance stakeholders to ensure alignment across initiatives.

Requirements

  • 3–5 years of experience in fraud, risk analytics, model governance, or a related role.
  • Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Engineering, or Computer Science, or equivalent experience.
  • Working knowledge of Model Risk Management (MRM) frameworks and model governance processes.
  • Strong analytical skills with experience evaluating model performance and identifying issues.
  • Proficiency in SQL and Python for data analysis and investigation.
  • Experience with fraud model performance metrics such as fraud capture rate, false positive rate, precision/recall, AUC, and drift monitoring.
  • Familiarity with data science workflows and working with datasets to support model analysis and validation.
  • Experience working with cross-functional stakeholders and external vendors.
  • Strong documentation skills, including preparing model documentation, monitoring reports, or audit responses.
  • Clear communication skills with the ability to translate technical concepts into business and compliance context.
  • Strong organizational and program management skills with the ability to manage multiple priorities.
  • Experience working with fraud models or contributing to fraud model development, preferred.
  • Familiarity with machine learning concepts and interpreting model outputs and performance tradeoffs, preferred.
  • Prior experience with vendor models such as identity, device, or fraud risk vendors, preferred.
  • Exposure to regulatory or compliance environments in financial services, preferred.
  • Experience with model monitoring frameworks or tools, preferred.

Benefits

  • Competitive base pay range, with final offer determined by experience, skills, and location.
  • Access to SoFi’s comprehensive and competitive benefits package.
  • Reasonable accommodations available for candidates with physical or mental disabilities.
  • Inclusive culture with equal employment opportunities for all applicants and employees.
  • Consideration for qualified applicants with arrest and conviction records under the San Francisco Fair Chance Ordinance.
  • Support for internal applicants through SoFi’s Internal Job Board.
  • Remote work is not currently accommodated from Hawaii or Alaska due to insurance coverage issues.

Interested in this position?

Apply directly on the company website

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