Quant Analyst - Credit Risk

Location

Vereinigte Staaten von Amerika | Germany

Job description

Quant Analyst - Credit Risk

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; and credit 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 Risk Analytics group (“QRA”) is responsible for all credit, market and liquidity risk related modelling. This includes, but is not limited to, the estimation of Probability of Default (PD) and Loss Given Default (LGD) for corporate, municipal and sovereign entities. 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 Quantitative Risk Analytics group has an open position in New York for an experienced Credit Risk quantitative analyst to develop Bloomberg's default risk and portfolio credit risk models. These models are used by clients for internal credit risk analysis, Basel regulatory capital calculations, and supporting IFRS9 regulations.

We will trust you to:

• Research, design, prototype, implement, test, document and support statistical/machine-learning and econometric credit risk models, including probability of default (PD), loss given default (LGD), exposure at default (EAD), and portfolio loss calculations
• 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, and risk product support unit, and engineers. This includes writing mathematical and technical documentation
• Assist the QRA Team Leader with Credit Risk project management. This includes coordination of fellow team members as well as collaboration with Engineering, Product Managers, and Model Validation partners
• Maintain Credit Risk methodology thought leadership. The Quant Analytics team sometimes publishes research papers in academic and industry journals

You will need to have:

• Ph.D in a quantitative field such as Mathematics, Physics, Engineering, or Quantitative Finance
• A minimum of 7+ years on a credit risk modeling team of a buy-side or sell-side institution*
• Hands-on experience in default risk modeling, credit related risk measures, regulations and accounting standards
• Demonstrable knowledge of probability theory, stochastic processes, probabilistic and machine learning techniques, statistical estimation and testing, Monte Carlo methods
• Proven 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 and delivery, team leadership, and communications with internal and external stakeholders and clients

We would love to see:

• Strong oral and written communication skills
• Collaborative mentality and enjoy working in teams with other quants, engineers, and product managers
• Familiarity with object-oriented design patterns and C++ programming

*Please note we use years of experience as a guide, but we will certainly consider applications from all candidates who are able to demonstrate the skills vital for the role.

If this sounds like you, please apply!

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Bloomberg is an equal opportunity employer, and we value diversity at our company. We do not discriminate based on age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. 

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