Quantitative Analytics Lead

Technical Skills:

• 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.

Complexity and Impact of Work:

• 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.

Organizational Knowledge:

• 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.

Communication and Influence

• 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.

You may be a fit for this role if you have:

• 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.

Although not a requirement, bonus points if:

• You’ve kept up to date with the proliferation of blockchain and crypto innovations.
• You were emotionally moved by the soundtrack to Hamilton, which chronicles the founding of a new financial system. :)