- The Sr. Risk Analyst will be responsible for developing strategies to optimize consumer strategy, primarily marketing and risk strategies with the intent to maximize unit economics, reduce defaults (losses) and increase the scale of the portfolio.
- Establish, maintain, and revise underwriting strategies by conducting statistical and other data mining analyses on data including portfolio history, credit & alternate data and credit & fraud models developed by decision sciences team. These statistical techniques include but are not limited to linear/logistic regression, CART, CHAID and other decision tree techniques.
- Establish, maintain, and analyze various Key Performance Indicators that reflect the unit economics and underlying portfolio profitability such as Revenue & Yield rates, Charge-offs and loss rates, Recovery, Customer Acquisition Costs (CAC) and other relevant metrics.
- Develop portfolio review materials on a periodic basis that captures key trends against benchmarks and analyze respective variance. Communicate to senior management and other credit committee members the key trends and general portfolio health.
- Analyze and recommend optimal product parameters such as loan amounts, interest rates and term based on target economics and performance metrics.
- Collaborates with internal business teams including marketing, product, decision sciences, and technology teams to implement the relevant portfolio strategies including but not limited to marketing and underwriting strategies, credit policy and loss mitigation strategies.
- Collaborates with the credit, marketing, product and loss mitigation teams to develop long term portfolio strategies.
- Develop testing framework, expectations on key metrics and analyze/measure against the key metrics. Portfolio tests typically include loan offers, underwriting strategies, account management strategies such as credit line increases, loan refinance and amendment programs.
- Present findings and make recommendations to Credit committee and portfolio management teams.
- Bachelor's degree in Statistics, Economics, Business, Operations Research, Mathematics, or a related highly quantitative degree required. Master's degree preferred.
- 2 -4 years previous experience in highly quantitative roles developing and recommending strategies using quantitative methods and justification.
- 2 -4 years previous experience in utilizing statistical techniques such as decision tree, logistic regression, hypothesis testing etc. required.
- Proficiency with SAS/R/Python, SQL, and Excel skills required.
- Ability to conduct extensive data research and handle large datasets.
- Experience in Financial Services, Risk Management, Subprime Lending, Marketing Analytics, Pricing, Direct Mail or Segmentation a plus.
- Must have strong problem-solving and organization skills with strong attention to detail and the ability to manage multiple projects.
- Excellent written and verbal communication skills.
- Team player who will work efficiently and effectively in a fast-paced environment.
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