Develop/Review models (traditional regressions as well as AI/ML based) to ensure fair banking compliance
Perform quantitative analysis to identify fair lending risks
Identify potential alternative ways to mitigate fair lending bias arising from models/policies
Develop specialized analytical tools for projects or ongoing use
Compile and generate ad-hoc analytical reports
Lead research efforts, applying expertise in statistical analysis and modeling
Provide advisory support to line of business model owners regarding best practices for compliance guided by policies and industry standards/methods
Lead cross-functional teams or projects with significant complexity
Independently manage end-to-end functional programs
Use sophisticated analytical mindset to exercise judgement and identify solutions
Communicate complex results to non-technical audience
Work autonomously as the lead and guide others within the area of expertise
Independently handle multiple projects and prioritize based on changing business needs

Requirements

3+ years relevant work experience or Undergraduate degree and 2+ years of relevant work experience.
Graduate's degree in a quantitative field is a plus.
Research experience is a plus.
Demonstrated experience in development of predictive models using Python
In-depth knowledge of quantitative models and statistical analysis.
Experience working with AI/ML based models.
Proficiency in Python is required.
Experience working with databases/datasets and data visualization tools (Tableau/Power BI)

Benefits

Health insurance
401(k) matching
Paid time off (including Vacation PTO, Flex PTO, and Holiday PTO)
Career development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

predictive modelingstatistical analysisquantitative analysisAI modelsML modelsPythondata visualizationdatabase managementregression analysisanalytical tools

Soft Skills

leadershipcommunicationproblem-solvingjudgmentautonomyproject managementcross-functional collaborationadvisory supportprioritizationresearch