Our client, a leading bank, is looking for a Fair Lending Analytics professional to join their growing team.
03rd May, 2022
Job Description & Synthesis
The Lending Analytics position will perform quantitative analyses to identify potential lending discrimination, describes the analyses to stakeholders (e.g., regulators, business units), and issues recommendations as needed.
Specific Responsibilities
Data science – Performs analyses, including linear and logistic regression models, comparisons of lending and branch distribution to peers and the market, and identification of statistically significant differences in loan application outcomes between protected classes and control groups.
Reporting – Describes analyses performed, findings, and recommendations in written reports and meetings with stakeholders.
Regulatory Expertise – Maintains strong familiarity with regulatory requirements pertaining to fair lending and unfair, deceptive, and/or abusive acts or practices, and advises the business units on related questions.
Other Projects – Assists the Fair and Responsible Banking Officer with updating policies and training materials, performing risk assessments, and reviewing marketing materials, legal disclosures, and complaints.
Key Qualifications
Bachelor's Degree and 5 years of experience in Compliance, Legal, or Audit OR High School Diploma or GED and 9 years of experience in Compliance, Legal, or Audit
License or Certification Type (PREFERRED): Certified Anti-Money Laundering Specialist (CAMS) or Certified Anti-Money Laundering and Fraud Professional (CAFP) or Certified Regulatory Compliance Manager (CRCM)
Preferred: Bachelor's and/or advanced degree in a quantitative field (e.g., Statistics, Mathematics) from a reputable school, with a minimum overall GPA of 3.3, and completion of at least one course in regression modeling.
At least four years of experience creating linear and logistic regression models using statistical software (e.g., Minitab, SAS), evaluating models, and correcting violations of model assumptions.
Excellent verbal, written, and analytical skills, including at least four years of experience analyzing large datasets, writing advanced Excel formulas, creating pivot tables, and simplifying technical matters for non-technical audiences.
Consistently strong work performance reviews in prior positions.