Compliance - Quant Modeling Senior Associate Fair Lending

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 90,000 - 130,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a quantitative analytics professional to develop and implement AI-enabled fair lending solutions.

You will work with Modeling, Data Science and Technology teams to deploy predictive methods, automate workflows, and strengthen governance across risk and compliance processes. The role requires 2+ years of experience and a strong foundation in statistics, ML, and cloud-based data platforms.

Qualifications

• Graduate degree in a quantitative field such as Statistics, Economics, CS, Engineering, Data Science or Mathematics.
• 2+ years of experience in statistics, data science, analytics, model review or related quantitative function.
• Proficiency in Python, shell scripting, cloud platforms and tools (AWS, Spark, Git/Bitbucket, Databricks) and databases (Snowflake, Hadoop, Teradata, Hive).
• Solid grasp of statistical concepts and methodologies for business and compliance questions.
• Experience developing and evaluating ML models to support business decisions.
• Experience applying data science and AI techniques to solve business problems.

Responsibilities

• Conduct research and develop analytical and technology solutions to enhance fair lending risk analysis.
• Leverage AI-enabled tools, generative AI, and automation to scale analytics and reduce manual effort.
• Collaborate with Modeling, Technology, Data Science and business teams to design and implement AI-enabled solutions.
• Evaluate and deploy advanced analytical capabilities to improve productivity and governance.
• Identify data needs and gaps, coordinating with lines of business for resolution.
• Develop statistical models to assess fair lending disparities and inform analytic strategies.
• Prepare model documentation, evaluate performance, and ensure compliance with governance standards.
• Support model reviews by assessing methodologies, assumptions, and performance metrics.
• Create presentations and reports for technical and non-technical audiences; engage with OFL, LOBs, Legal, IT, and Governance.
• Perform other related duties as assigned.

Skills

Statistics

Data Science

Machine Learning

Critical thinking

Communication skills

Team collaboration

Education

Graduate degree in a quantitative field (Statistics, Economics, Computer Science, Engineering, Data Science, Mathematics)

Tools

Python

Shell scripting

AWS

Spark

Git/Bitbucket

Databricks

Snowflake

Hadoop

Teradata

Hive

Job description

Job Responsibilities

• Conduct research and develop innovative analytical and technology solutions to enhance fair lending risk analysis methodologies, improve process efficiency, and keep the fair lending compliance program aligned with industry and regulatory standards.

• Leverage AI-enabled tools, generative AI, intelligent automation, and emerging technologies where appropriate to scale analytical capabilities, improve effectiveness, and reduce manual effort across fair lending processes.

• Partner with Modeling, Technology, Data Science, and business teams to design, develop, and implement AI-enabled solutions, including intelligent agents, automated analytical workflows, and reusable tools that support fair lending analytics and model review processes.

• Evaluate, prototype, and deploy advanced analytical and AI-driven capabilities that enhance productivity, improve transparency, strengthen controls, and support scalable execution of compliance and risk-management activities.

• Identify, request, and review relevant data to support ongoing and ad hoc fair lending analysis projects; identify potential gaps between data available for analysis and business policy requirements, such as underwriting attributes, and follow up with lines of business for resolution.

• Develop and apply statistical models and techniques to evaluate potential fair lending disparities across lines of businesses; review and assess business policies, practices, and procedures to inform analytic strategies; develop quantitative and statistical models; perform independent analysis to assess fair lending risks; and make recommendations for fair lending testing.

• Prepare and maintain model documentation, evaluate model performance, and ensure compliance with Model Risk Governance and Review standards.

• Support model review activities by assessing model methodologies, assumptions, segmentation approaches, performance metrics, and potential fair lending implications.

• Prepare presentations and reports to communicate analytical results, solution designs, and innovation initiatives to technical and non-technical audiences; engage with stakeholders including OFL partner teams, lines of business (LOBs), Legal, Technology, Data Science, IT, and Model Governance.

• Perform other related duties as assigned.

Required Qualifications, Capabilities and Skills

• Graduate degree in a quantitative field, such as Statistics, Economics, Computer Science, Engineering, Data Science, Mathematics, or a related discipline.

• 2+ years of experience in statistics, data science, business analytics, model review, or a related quantitative function.

• Proficiency in Python, shell scripting, cloud computing platforms and tools (e.g., AWS, Spark, Git/Bitbucket, databricks) and database systems (e.g., Snowflake, Hadoop, Teradata, Hive).

• Deep understanding of statistical concepts and methodologies, with the ability to apply them effectively to complex business and compliance questions.

• Experience developing, implementing, and evaluating machine learning models with demonstrated ability to select appropriate modeling techniques, validate model performance, and interpret results to support business decision-making.

• Experience applying data science, automation, artificial intelligence, machine learning, or advanced analytics techniques to solve business problems.

• Strong critical thinking and analytical skills, with the ability to manage multiple projects in a fast-paced environment while maintaining a focus on quality.

• Willingness to learn, adapt to changes, and work collaboratively as a team player.

• Excellent verbal and written communication skills, with the ability to clearly present complex and sensitive issues to both technical and non-technical audiences.

Preferred Qualifications

• Experience developing AI-enabled business solutions using generative AI, large language models (LLMs), retrieval-augmented generation (RAG), agentic systems, workflow automation platforms, or machine learning techniques.

• Experience building proof-of-concepts and production-ready solutions that improve operational effectiveness, analytical capabilities, controls, or user experience.

• Knowledge of cloud-based analytics, data engineering, or AI platforms is a plus.

• Experience with BI, GIS, or automation tools such as Tableau, ArcGIS, or Alteryx is a plus.

• Experience in fair lending or responsible banking is a plus.