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.