Compliance - Quant Modeling Associate Senior - Associate

3 weeks ago

Jersey City, United States JPMorgan Chase & Co. Full time

Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

JPMorgan Chase and Co. (JPMorgan Chase) is committed to provide fair, equitable, and nondiscriminatory access to credit for both individuals and communities. This commitment is part of our fundamental mission of providing quality financial services to existing and prospective customers in accordance with all applicable laws and serving unique customers. To accomplish this, the Office of Fair Lending (OFL) has a very robust Fair Lending function that oversees firm’s compliance with fair lending laws.

Office of Fair Lending is seeking a qualified Fair Lending Quant Modeling Associate Senior to perform statistical modeling and analyses to support the firm’s fair lending monitoring. This individual will also participate in related research projects to support & enhance the bank’s fair lending compliance program.

Job Responsibilities: 

As a Fair Lending Quant Modeling Associate Senior in this high-visibility role, you will:

Understand lifecycle of mortgage lending and publicly available sources of data and information (., Home Mortgage Disclosure Act – HMDA LAR)  Understand fair housing laws and regulations (., Equal Credit Opportunity Act; Fair Housing Act; Dodd Frank Act) and regulatory guidance (Consumer Financial Protection Bureau, Office of Comptroller of Currency) on evaluating disparate impact and disparate treatment in home lending. Review and understand business policies, practices, and procedures to inform analytic strategies for fair lending monitoring; develop statistical tools for decision-making.  Identify, request, and review relevant data from appropriate parties to support ongoing and adhoc fair lending analysis projects as data-user; make recommendations to OFL leadership. Develop appropriate regression models and statistical techniques to evaluate potential fair lending disparities in underwriting and pricing decisions for JPMC home lending lines of business (LOBs) – Asset Wealth Management; Branch and Specialty Sales; Correspondent, etc., including Servicing and Subservicing activity (., loss mitigation; modifications). Prepare and update model documentation of fair lending models, evaluate model performance, and adhere to Model Risk Governance and Review standards.  Perform research and development to keep the fair lending compliance program abreast with industry and regulatory standards. Present results to peers and department leaders. Prepare presentations and reports to explain analytical results in both non-technical and technical formats to various partners; engage with stakeholders such as Office of Fair Lending partner teams, LOBs, Legal, Model governance; Compliance Conduct and Operation Risk (CCOR) Chief Data Office etc. Peer review analytic projects. Perform other related duties as assigned.

Required Qualifications, Capabilities, and Skills:

Minimum education and experience required: Master’s degree or equivalent in Statistics, Economics, Decision Science, Operations Research, Mathematics, or a related quantitative field plus two (2) years of experience in data extraction, manipulation and regression modeling using statistical software; or related experience OR . or equivalent in Statistics, Economics, Decision Science, Operations Research, Mathematics, or a related quantitative field plus zero (0) years of experience. Demonstrated knowledge of formal statistical and econometric analysis including linear, logistic regression modeling and non-parametric testing.  Demonstrated knowledge of Microsoft Word, Excel, and PowerPoint tools. Experience synthesizing and analyzing diverse information and developing strategy recommendations from observed outcomes.  Experience in SAS / Python / R; Experience with bias detection tools or research of fairness; data manipulation and analysis. Strong critical thinking and analytical skills; ability to work in a fast-paced environment; be a team player; and manage multiple projects towards completion with focus on quality. Good communication skills both verbal and written; ability to communicate technical matters in a non-technical way and clearly present complex and sensitive issues. Knowledge of data screening, geocoding, and mapping tools (., Tableau; ArcGIS); knowledge of statistical sampling methodologies for comparative file review (., matched-pair sampling). 

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