Responsibilities:
- Own, enhance, implement, and maintain the OneMain’s Fair Lending Analytics Program, ensuring appropriate Fair Lending statistical analyses are conducted accurately and timely to mitigate fair lending risk across our products.
- Collaborate across multidisciplinary teams - Legal & Compliance, Data Science, Model Risk Management and Operations.
- Proactively learn business model changes including various underwriting and pricing strategies that could introduce fair lending risk across customer life cycle from customer acquisition to servicing.
- Use various statistical techniques like regression and classification tests to report on potential risk areas and perform statistical deep dives to enhance analysis. Build metrics around both statistical and practical significance by building compelling analytical arguments and statistical models.
- Draft clear and concise reports of the results of ongoing monitoring and special assessment projects and present results to Compliance organization
- Provide consulting services to business partners on issues involving identification of realized and emerging fair lending risks.
Qualifications:
- 4+ years' experience in statistics, data science, decision science, or a related quantitative field
- Masters degree required
- 2+ years experience building statistical models in consumer finance industry
- 3+ years experience with fair lending-related testing, including the following techniques:
- BISG algorithm
- Feature/variable proxy testing
- Shapley or related model proxy testing
- Statistical significance model proxy testing
- Classical and non-parametric statistical techniques as applicable
- Knowledge of consumer lending products and practices.
- Working knowledge of US fair lending laws (ECOA, UDAAP etc)
- Working knowledge of machine learning models, specifically tree models like XGboost.
- Familiarity with Large Language Models (LLM) is desirable
- Excellent analytical and deep dive skills using data analysis and model building.
- Strong ability to create new statistical procedures and metrics to address business problems.
- Excellent presentation and communication skills, including technical writing abilities.
- Strong ability to communicate effectively with colleagues with varying degrees of technical analytics knowledge and experience.
- Strong problem-solving skills
- Strong idea generation and deep-thinking skills with interest in R & D
- Proficient in Python/SAS, SQL and general database skills
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