Quant Analyst – Market Risk

Details

Bloomberg’s Quantitative Analytics team designs and implements modeling analytics that support client pricing and risk management solutions for financial products across Bloomberg’s products and services. The team develops models for derivative pricing, market data, counterparty credit, XVA, initial margin, Value-at-Risk, market risk, credit risk, and climate risk, using modern C++ and Python libraries.

The Quantitative Market and Liquidity Risk Analytics group is responsible for market and liquidity risk modeling, including stress testing, VaR, stressed VaR, tail-risk measures, regulatory capital calculations, CCAR scenarios, FRTB, SIMM, and liquidity assessment. The group conducts model research and development and deploys models into production in collaboration with Model Validation, Engineering, and Product Management teams.

Responsibilities

• Research, design, prototype, implement, test, document, and support statistical, machine-learning, and econometric Market Risk models.
• Support the integration and release of quantitative code into production systems in collaboration with Model Validation and Engineering teams.
• Communicate modeling concepts and assumptions to external clients, product managers, sales, risk product support, and engineering teams.
• Write technical documentation and deliver presentations to a variety of audiences.
• Assist the QMLRA Team Leader with Market Risk project management, including coordinating team members and collaborating with Engineering, Product Managers, and Model Validation partners.
• Maintain Market Risk methodology thought leadership and contribute to research papers published in academic and industry journals.

Requirements

• Ph.D. or equivalent experience in Mathematics, Statistics, Physics, Engineering, Quantitative Finance, or a related quantitative field.
• Four or more years of experience at VP level or above on a Market Risk modeling team at a buy-side or sell-side institution, or at an equivalent level at a vendor.
• Hands-on experience in Market Risk modeling, including knowledge of risk measures, financial products, and derivatives. Expertise is required in at least two asset classes.
• Fluency in relevant regulatory and non-regulatory Market Risk calculations.
• Knowledge of probability theory, stochastic processes, probabilistic and machine-learning techniques, statistical estimation and testing, Monte Carlo methods, numerical analysis, and linear algebra.
• Experience with Natural Language Processing techniques such as sentiment analysis, topic modeling, text classification, semantic analysis, and named entity recognition. Experience with agentic modeling is a bonus.
• Proven C++ and Python programming and software engineering skills, including code design, implementation, testing, and production release.
• Working knowledge of common data science libraries.
• Hands-on experience with project management, execution, delivery, and communication with internal and external stakeholders and clients.
• Strong oral and written communication skills and the ability to work with quants, engineers, and product managers.
• Passion for capital markets, finance, and economics.
• Intellectual curiosity and the ability to develop new approaches to complex problems.

Benefits

Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, and vision coverage, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs.