Anchorage Digital is seeking a Model Validation and Research Quant to oversee the Model Risk Management program and provide expert guidance for capital planning, risk management, and regulatory matters within their Economic & Regulatory Analysis pillar.
Requirements
- Proficiency in a programming language such as Python, R, etc.
- Experience in SQL programming and working with large data sets.
- Skills in statistics or quantitative modeling (stochastic and econometric), research, and data analysis.
- Experience in risk management methods (e.g., VaR, expected shortfall, stress testing, backtesting, scenario analysis).
- Hands-on experience in the entire model development lifecycle including research, implementation, ongoing monitoring, and production maintenance.
- Experience in writing, editing, or reviewing technical documents suitable for regulatory or banking context.
Responsibilities
- Drive model validation work independently, including leading from end-to-end with little oversight and coordinating activities of other team members.
- Assist with implementing and maintaining sound model governance, which includes model controls, inventory, reporting, and policies and procedures.
- Perform quantitative analytics and research to support business operations, financial forecasts, capital planning, risk management, and regulatory compliance.
- Assist in development and maintenance of statistical models relevant for market risk, credit risk, and stress testing purposes, including margin, pricing, and VaR applications.
- Participate in all aspects of the model life cycle, including design, implementation, testing, production, validation, and performance monitoring.
Other
- Masters or Ph.D. degree in a quantitative field such as statistics, applied mathematics, economics, quantitative finance, and operations research.
- Direct work experience in compliance modeling and systems, risk measurement and management, and regulatory capital requirements.
- Have a deep knowledge of the strategy of Anchorage Digital and its various business lines.
- Familiarity with U.S. banking regulatory requirements and supervisory expectations, and understand their impact on the organization.
- Demonstrate capability in writing, editing, or reviewing technical documents suitable for various contexts as relevant (e.g., regulatory or banking, internal or external stakeholders).
- Produce clear reports and presentations describing quantitative analytics projects and their results, interpreting them for senior management.
- Provide formal or on-the-job training to other staff on technical topics.
