Data Scientist-Credit Risk Analytics

1 week ago

Draper, UT, United States BAMM USA Full time
JOB PURPOSE

We're expanding our Risk Analytics team and ARE seeking a Data Scientist specializing in credit risk modeling and portfolio analytics. In this role, you'll leverage advanced analytics, machine learning, and statistical modeling to assess risk, optimize underwriting, and drive portfolio performance. You'll collaborate closely with risk, product, and data science teams to design proactive solutions, monitor credit health, and deliver insights that influence key business decisions. The work you do will have an immediate and lasting impact on customer accessibility, portfolio profitability, and long-term growth.

KEY RESPONSIBILITIES
  • Develop, validate, and deploy credit risk strategies (underwriting, scorecards, loss forecasting) using Python and ML frameworks (Scikit-learn, XGBoost, etc.).
  • Engineer and optimize credit risk features (e.g., payment behavior, utilization patterns, external credit bureau data).
  • Monitor portfolio performance trends and build dashboards to assess delinquency, loss rates, and risk-adjusted returns.
  • Partner with Risk leadership to design policies balancing credit growth, customer access, and portfolio stability.
  • Share data-driven insights with senior leadership to shape credit risk strategy.
  • Support stress testing, risk segmentation, and scenario analysis to inform decision-making.
REQUIRED QUALIFICATIONS
  • Bachelor's or advanced degree in Data Science, Mathematics, Computer Science, Statistics, Economics, or related field
  • 5+ years' experience programming in Python (NumPy, Pandas, Scikit-learn, XGBoost)
  • 2+ years' experience with SQL
  • Experience in credit risk analytics, underwriting, or portfolio management
  • Strong ability to balance growth, risk exposure, and profitability
  • Excellent problem-solving and independent work skills
PREFERRED QUALIFICATIONS
  • Experience with credit bureau data (e.g., Equifax, Experian, TransUnion)
  • Understanding of credit lifecycle processes (originations, collections, recovery, loss forecasting)
  • Knowledge of credit risk modeling techniques (scorecards, logistic regression, machine learning)
  • Familiarity with regulatory and compliance considerations in credit decisioning
  • Master's degree or higher in a quantitative discipline
COMPENSATION/BENEFITS
  • Full health benefits-Medical/Dental/Vision
  • 401(k) match, 6%/3%
  • DTO (discretionary time off)
  • Health savings account (HSA) with company contribution
  • College tuition reimbursement program (STEAM degrees)
  • Unlimited use of Linkedin Learning
  • Free car charging
  • Onsite gym and showers

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