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
• 4+ years' experience in statistics, data science, decision science, or a related quantitative field
• Masters degree required
• 3+ years experience with fair lending-related testing, including the following techniques:
o BISG algorithm
o Feature/variable proxy testing
o Shapley or related model proxy testing
o Statistical significance model proxy testing
o Classical and non-parametric statistical techniques as applicable
• Knowledge of consumer lending
• Working knowledge of machine learning models, specifically tree models like XGboost.
• Excellent analytical and deep dive skills using data analysis and model building.
• SQL/SAS/Python
Skill
Modeling, Python, SQL
Minimum Qualification
MSc