Quant Analyst - Market Risk

Bloomberg; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Bloomberg's Quantitative Analytics team in New York seeks an experienced Market Risk quantitative analyst to research, prototype, document, and support Market Risk models across asset classes, including derivatives pricing, VaR and regulatory measures.

You will collaborate with Validation and Engineering, help deploy code to production, communicate technical concepts to clients and product teams, and contribute to project management and thought leadership through occasional research publications.

Qualifications

• Ph.D. or equivalent in a quantitative field.
• 4+ years of VP-level or equivalent Market Risk modeling experience.
• Expertise in multiple asset classes and regulatory calculations.
• Strong programming skills in C++ and Python.
• Experience with NLP techniques and ML in finance.
• Excellent communication and collaboration skills.

Responsibilities

• Research, prototype, implement, test, and document Market Risk models.
• Support production deployment with Validation and Engineering teams.
• Communicate modeling concepts to clients, product managers, and engineers.
• Coordinate team efforts and manage projects within QMLRA.
• Maintain thought leadership through publishing research.

Skills

C++ programming

Python programming

Market Risk modeling

Statistical methods

Machine learning

Quantitative finance

Project coordination

Communication

Documentation

NLP

Education

Ph.D. or equivalent in Mathematics/Statistics/Physics/Engineering/Quantitative Finance

Tools

C++

Python

Monte Carlo

Data analysis libraries

Job description

Bloomberg's Quantitative Analytics team is responsible for the design and implementation of modeling analytics that support client pricing and risk management solutions for financial products across the entire suite of Bloomberg products and services, including its terminal with 300,000+ clients, trading system solutions, buy- and sell-side enterprise risk management, and derivatives valuation services. These models include those for pricing derivative products across all major asset classes, including market data; counterparty credit, XVA and initial margin; Value-at-Risk and other Market Risk metrics; Credit Risk models, and Climate Risk models. The team has two recent Risk Quant of the Year winners and is dedicated both to novel research as well as efficient model delivery through modern C++ and Python libraries.

Within the Quantitative Analytics team, the Quantitative Market and Liquidity Risk Analytics group ("QMLRA") is responsible for all market and liquidity risk related modeling. This includes, but is not limited to, stress testing, including modelling of various stress scenarios for cash and derivatives portfolios, VaR, stressed VaR and various tail-risk measures, regulatory capital calculations, CCAR scenarios, FRTB, SIMM, and liquidity Assessment. The group is responsible for model research and development, as well as model deployment into production in collaboration with our Model Validation, Engineering, and Product Manager partners

The QMLRA group has an open position in New York for an experienced Market Risk quantitative analyst to support our growing client business. The candidate will be responsible for researching, and prototyping models, documenting models, planning project execution, and coordination of team members.

We will trust you to:

• Research, design, prototype, implement, test, document and support statistical, machine-learning, and econometric Market Risk models
• Support the integration and release of quant code into production systems in association with our Model Validation and Engineering partners
• Communicate modeling concepts and assumptions to external clients, product managers, sales, the risk product support unit, and engineering teams. This includes writing technical documentation and delivering presentations to a variety of audiences
• Assist the QMLRA Team Leader with Market Risk project management. This includes coordination of fellow team members as well as collaboration with Engineering, Product Managers, and Model Validation partners
• Maintain Market Risk methodology thought leadership. The Quant Analytics team sometimes publishes research papers in academic and industry journals

You will need to have:

• Ph.D. or equivalent experience in a quantitative field such as Mathematics, Statistics, Physics, Engineering, or Quantitative Finance
• Work experience at VP level or above (4+ years) at a Market Risk modeling team of a buy-side or sell-side institution, or at the equivalent level at a vendor
• Hands-on experience in Market Risk modeling, understanding of risk measures, familiarity with financial products and derivatives (expertise needed in at least two asset classes), along with fluency in the relevant regulatory and non-regulatory Market Risk calculations
• Knowledge of probability theory and stochastic processes, probabilistic and machine learning techniques, statistical estimation and testing, Monte Carlo methods, numerical analysis, and linear algebra
• Experience with Natural Language Processing modeling techniques, e.g. Sentiment Analysis, Topic Modeling, Text Classification, Semantic Analysis, and Named Entity Recognition. Proficiency with agentic modeling is a bonus
• Proven C++ and Python programming and software engineering skills. This includes code design, implementation, testing and production release, as well as working knowledge of common data science libraries
• Hands-on experience in project management, execution and delivery, and communications with internal and external stakeholders and clients

We would love to see:

• Strong oral and written communication skills. You enjoy working in teams with other quants, engineers, and product managers
• Passion about the Capital Markets, Finance, and Economics
• High-level of intellectual curiosity and demonstrated capability to generate new and interesting approaches to solving complex problems