AVP - Fair Lending , Quant Modeling

CCOR Fair Lending Quant Modeling Associate Senior

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.

Compliance's Office of Fair Lending

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.

Job Summary

Office of Fair Lending is seeking a qualified Fair Lending Quant ModelingAssociate Seniorto perform statistical modeling and analyses to detect & mitigate bias in line-of-business models. This individual will also participate in bias testing-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:

• Conduct statistical analyses and bias testing to review business models, including both traditional and machine learning / artificial intelligence models (ML/AI),for fair lending compliance
• Build data-driven algorithms to mitigate potential disparate impact of models by working alongside model developers, business strategy owners & Legal to develop less discriminatory alternative models
• Prepare presentations & reports to explain statistical results in both non-technical and technical formats to various stakeholders such as senior management, Legal, Model developers, Model Governance etc.
• Perform research & development to keep the fair lending compliance program aligned with industry and regulatory standards
• Create model documentation work with Control, Audit and Model Governance teams to ensure adequacy of processes, statistical models and model reviews
• Support the team in maintaining relevant policies & procedures and representing fair lending in regulatory exams, audits and other areas related to internal governance
• Perform other related duties as assigned

Required Qualifications, Capabilities, and Skills:

• Bachelor degree required in a quantitative field(e.g., Statistics, Economics, Computer Science, Engineering) with 8+ years of relevant work experience, or Masters degree in a quantitative field with 6+ years of relevant work experience
• Entrepreneurial spirit, strong attention to detail, ability to take the lead on projects, in depth interest in solving complex business problems with data and passion for spreading a culture of change towards data-driven decision making
• Proficiency in Python , shell scripting, cloud computing platforms and tools (e.g., AWS, Spark) and database systems (e.g., Hadoop, Teradata, Hive)
• Experience in developing, implementing evaluating linear / logistic regressionandmachine learning / artificial intelligence models
• Experience working or consulting for a bank, a consumer financial product company such as a non-depository mortgage lender or fintech, a banking regulator (e.g., OCC, CFPB) or other similar government regulatory or enforcement agencies with knowledge of how consumer financial products such as mortgage and auto loans are underwritten and priced
• Strong project management , critical thinking and analytical skills ability to work in a fast-paced environment and manage multiple projects towards completion with focus on quality
• Excellent communication skills both verbal and writtenability to communicate technical matters in a non-technical way & clearly present complex and sensitive issues

Preferred Qualifications, Capabilities, and Skills:

• Experience in SAS
• Experience with bias detection tools or research of fairness