Senior Quantitative Risk Analyst (Internal Audit - Model & AI Governance)

Responsibilities

• Leads IA’s assessment of the design, development, validation, and implementation of advanced quantitative models, analytics strategies and AI products.
• Ability to evaluate approaches to assess model performance, scalability, robustness, bias, sensitivity, and risk under varying assumptions or operating conditions across model and AI products.
• Partners with cross functional teams to assess management’s alignment of quantitative solutions with business objectives, technical feasibility, and implementation priorities.
• Mentors junior team members on modeling techniques, coding practices, documentation standards, and analytical storytelling.
• Develops and advances reusable frameworks, technical standards, and best practices that improve the quality and efficiency of IA quantitative analytics work.
• Communicates complex concepts, tradeoffs, and recommendations to senior stakeholders in a clear, practical, and decision-oriented manner.
• Identifies high value analytical opportunities and defines appropriate methodologies to address complex, ambiguous problems.

Qualifications

• Bachelor’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.
• 5+ years of experience in analytics, mathematics, statistics, computer science, data science, operations research, economics, finance.
• Complete knowledge and understanding of business area/specialization.
• Advanced knowledge of quantitative modeling, optimization, statistical inference, machine learning, simulation, or algorithm design.
• Strong programming skills and experience building production quality analytical tools, data pipelines, models, or decision support systems.
• Demonstrated ability to lead complex analyses from problem definition through implementation and stakeholder adoption.
• Strong communication, influence, and consultative problem-solving skills.

Desired Qualifications

• Prior experience independently assessing and challenging model risk management, data governance and AI/Agentic governance within risk management or internal audit environments.
• Understanding of various models and modeling practices used in credit risk management, fraud detection, BSA/AML, operations, treasury & finance, marketing models, etc.
• Deep 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.
• Knowledge of one or more regulations and frameworks such as CECL, CCAR, BSA/Anti-Money Laundering, ECOA, FCRA, etc.
• Programming, data modeling, simulation, and advanced mathematics
• Familiarity with coding languages such as SQL, R, Python, Hadoop, or SAS.
• Knowledge 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.
• Master's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or another quantitative or related field.

Hours

Locations

• 820 Follin Ln. Vienna, Virginia 22180
• 141 Security Drive Winchester, VA 22602
• 5550 Heritage Oaks Dr. Pensacola, FL 32526

Company