Provide independent assurance over data science, machine learning, generative AI, and agentic AI capabilities through audit engagements and technical reviews. Evaluate model, AI and data governance frameworks, lifecycle controls, and oversight effectiveness, including risks associated with model complexity, uncertainty, and operational performance. Lead quantitative analyses that inform risk management activities and serve as a subject matter expert in model design, data-driven experimentation, and scalable analytical solutions. Advise Internal Audit staff, senior management, and business partners on AI/model lifecycle management, data governance, regulatory expectations, and industry practices. Conduct and manage increasingly complex projects with moderate supervision and independent judgment. This position is eligible for the TalentQuest employee referral program. If an employee referred you for this job, please apply using the system-generated link that was sent to you. Responsibilities 37Leads IA's assessment of the design, development, validation, and implementation of advanced quantitative models, analytics strategies and AI products.37Ability to evaluate approaches to assess model performance, scalability, robustness, bias, sensitivity, and risk under varying assumptions or operating conditions across model and AI products.37Partners with cross functional teams to assess management's alignment of quantitative solutions with business objectives, technical feasibility, and implementation priorities.37Mentors junior team members on modeling techniques, coding practices, documentation standards, and analytical storytelling.37Develops and advances reusable frameworks, technical standards, and best practices that improve the quality and efficiency of IA quantitative analytics work.37Communicates complex concepts, tradeoffs, and recommendations to senior stakeholders in a clear, practical, and decision-oriented manner.37Identifies high value analytical opportunities and defines appropriate methodologies to address complex, ambiguous problems. Qualifications 37Bachelor's degree in analytics, mathematics, statistics, computer science, data science, operations research, economics, finance or the equivalent combination of education, training or experience; Master's/advanced Degree preferred.375+ years of experience in analytics, mathematics, statistics, computer science, data science, operations research, economics, finance.37Complete knowledge and understanding of business area/specialization.37Advanced knowledge of quantitative modeling, optimization, statistical inference, machine learning, simulation, or algorithm design.37Strong programming skills and experience building production quality analytical tools, data pipelines, models, or decision support systems.37Demonstrated ability to lead complex analyses from problem definition through implementation and stakeholder adoption.37Strong communication, influence, and consultative problem-solving skills. Desired Qualifications: 37Prior experience independently assessing and challenging model risk management, data governance and AI/Agentic governance within risk management or internal audit environments.37Understanding of various models and modeling practices used in credit risk management, fraud detection, BSA/AML, operations, treasury & finance, marketing models, etc.37Deep knowledge and experience with model risk regulatory guidance; e.g., SR 11-7, SR 26-2, ASOP 56, as well as developing AI frameworks including NIST AI Risk Management Framework, and ISO/IEC 42001Artificial Intelligence Management System.37Knowledge of one or more regulations and frameworks such as CECL, CCAR, BSA/Anti-Money Laundering, ECOA, FCRA, etc.37Understanding of various models and modeling practices used in credit risk management, fraud detection, BSA/AML, operations, treasury & finance, marketing models, etc.37Programming, data modeling, simulation, and advanced mathematics37Familiarity with coding languages such as SQL, R, Python, Hadoop, or SAS.37Knowledge of AI platforms and data ecosystems supporting machine learning, generative AI, analytics, and LLM-enabled systems, including Microsoft Copilot Studio, Azure AI Foundry, AWS, Databricks and PowerBI.37Master's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or another quantitative or related field. Additional Information Hours: 37Monday - Friday, 8:00AM - 4:30PM Locations: 37820 Follin Ln. Vienna, Virginia 2218037141 Security Drive Winchester, VA 22602375550 Heritage Oaks Dr. Pensacola, FL 32526