• Proficiency in quantitative modeling (stochastic and econometric), research, and data analysis
• Extensive knowledge in risk management methods (e.g., VaR, expected shortfall, stress testing, backtesting, scenario analysis)
• Able to read and write code using a programming language (e.g., Python, R, Julia, etc.) in a collaborative software development setting
• A high level of proficiency in SQL programming and working with large data sets
• Masters or Ph.D. degree in a quantitative field such as statistics, applied mathematics, economics, quantitative finance, and operations research
• Strong quantitative skills and deep understanding of the following technical areas: 1) financial mathematics (e.g., derivatives pricing models, stochastic calculus, advanced linear algebra); 2) econometrics (e.g., time series analysis, GARCH, copula, etc.) and machine learning techniques; and 3) numerical methods and optimization (e.g., Monte Carlo simulation and finite difference techniques)
• Direct work experience in financial risk modeling, risk measurement and management, and regulatory capital requirements
• 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

Desirable

• As the Quantitative Analytics Lead for the Global Analytics team at Anchorage, you will take charge of spearheading the development and implementation of sophisticated models and methodologies aimed at the quantification of risk
• Additionally, you will be responsible for providing comprehensive quantitative analysis along with other forms of analytical support to meet the firm's diverse business needs
• The role demands a high degree of versatility because it involves steering and managing a variety of quantitative analytics projects
• Furthermore, it requires effective communication across both quantitative and non-quantitative audiences
• You will be responsible for leading a team of technical experts who are engaged in developing statistical models relevant for market risk, credit risk, and stress testing purposes
• In this capacity, you will be recognized as the go-to expert for quantitative analytics, shaping innovative solutions with your strategic insights, and fostering the technical expertise within the Global Analytics team
• We have created the Factors of Growth & Impact to help Villagers better measure impact and articulate coaching, feedback, and the rich and rewarding learning that happens while exploring, developing, and mastering the capabilities and contributions within and outside of the Quantitative Analytics Lead role:
• Develop and maintain 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
• Perform quantitative analysis to support business operations and financial forecasts, including data analytics and statistical/econometric modeling
• Because of the need to build and mature certain analytics and new products, work is not clearly defined and may lack strategic direction requiring a thoughtful approach
• Capable of breaking down large projects and processes into smaller tasks, and accurately estimating their time and scope. Articulate effectively the different options considered, analyze trade-offs, justify and define priorities
• Have a deep knowledge of the strategy of Anchorage Digital and its various business lines
• Possess strategic thinking and vision, with the ability to develop and implement a comprehensive quantitative analytics strategy aligned with organizational goals and objectives
• Prepare and deliver clear, accurate, and concise communication orally and in writing for quantitative and non-quantitative audiences
• Build effective relationships and rapport with stakeholders including cross-functional partners and external partners
• Communicate, organize and execute on cross-team goals and projects, utilizing relationships and resources cross-functionally to solve problems