Compliance - Quant Modeling Senior Associate Fair Lending
On-siteJersey City, New Jersey, United States
Job Summary
Conduct research and develop innovative analytical and technology solutions to enhance fair lending risk analysis methodologies and align the compliance program with industry standards. Leverage AI-enabled tools, generative AI, and intelligent automation to scale analytical capabilities and reduce manual effort across fair lending processes. Partner with Modeling, Technology, and Data Science teams to design, develop, and implement AI-driven solutions, including automated workflows and reusable tools that support fair lending analytics. Evaluate, prototype, and deploy advanced analytical capabilities to improve transparency, strengthen controls, and support scalable execution of compliance activities. Identify data gaps between available analytics and business policy requirements, then develop statistical models to evaluate potential fair lending disparities and assess business practices. Prepare model documentation, evaluate performance against Model Risk Governance standards, and communicate analytical results to technical and non-technical stakeholders.
Required Qualifications
- 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.
Desired 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.
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