Interest Rate Quant
Interest Rate Quant
Job Requisition Number: 37006
United States
New York - USA
The Role:
Bloomberg's Cross-Asset Derivatives Quant Team is responsible for modeling, implementing and deploying derivatives pricing models across all asset classes (FX, Equity, Rates, Commodity, Credit) to the entire suite of Bloomberg products and services, including its terminal with 300,000+ clients, trading system solutions, enterprise risk management, and derivatives valuation service. The group ensures that state-of-the-art models driven by high quality market data are brought together in robust, fast and accurate implementations that keep Bloomberg at the cutting edge of derivatives analytics.
The team seeks a Quant experienced in both pricing and data modeling for a cross-asset
team. The immediate need calls for experience in Interest Rate and Inflation Derivatives, but any cross-asset experience is a plus. The candidate will be responsible for:
- Designing algorithms for the automatic and statistical validation of market data from Bloomberg sources and contributors, and their aggregation into composite sources.
- Building quantitative models to calibrate curves, volatility surfaces and cubes to these sources for use in pricing models.
- Attributing pricing and hedging discrepancies appropriately to market data artifacts; and
communicating these findings to internal and external clients as necessary.
The candidate will be responsible for all aspects quant activities ranging from model research and prototyping to production implementation, deployment, and on-going maintenance, as well as interaction with internal and external clients.
Qualifications:
- Three to six years of experience with interest rate and inflation derivatives pricing and data modeling.
- On the pricing side, key requirements are mathematical finance, experience with models in interest rate and inflation derivatives and knowledge of numerical methods.
- On the data modeling side, experience with methodologies for curve, volatility surface and volatility cube construction including the validation and manipulation of market data used in this process. Experience in time series and statistics is a plus.
- Strong knowledge of interest rate and inflation products and market conventions.
- Strong C/C++ programming skills in a production environment required.
- Strong oral and written communication skills and ability to thrive in a multi-programmer team environment.
- Ph.D. in mathematics, finance, physics, engineering or related field.
The Company:
Bloomberg, the global business and financial information and news leader, gives influential decision makers a critical edge by connecting them to a dynamic network of information, people and ideas. The companys strength delivering data, news and analytics through innovative technology, quickly and accurately is at the core of the Bloomberg Professional service, which provides real time financial information to more than 310,000 subscribers globally. Bloombergs enterprise solutions build on the companys core strength, leveraging technology to allow customers to access, integrate, distribute and manage data and information across organizations more efficiently and effectively. Through Bloomberg Law, Bloomberg Government, Bloomberg New Energy Finance and Bloomberg BNA, the company provides data, news and analytics to decision makers in industries beyond finance. And Bloomberg News, delivered through the Bloomberg Professional service, television, radio, mobile, the Internet and two magazines, Bloomberg Businessweek and Bloomberg Markets, covers the world with more than 2,300 news and multimedia professionals at 146 bureaus in 72 countries. Headquartered in New York, Bloomberg employs more than 15,000 people in 192 locations around the world.
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Bloomberg is an equal opportunity/affirmative action employer and we welcome applications from all backgrounds regardless of race, color, religion, sex, national origin, ancestry, age, marital status, sexual orientation, gender identity, veteran status, disability, or any other classification protected by law.
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