Credit Financial Engineer for OTC Derivatives
Credit Financial Engineer for OTC Derivatives Structured Products Valuation and Risk Service
Job Requisition Number: 38383
United States
New York - USA
The Role:
The Financial Engineering group (part of our Bloomberg Core OTC Derivatives/Structured Notes Product group) is seeking market practitioner oriented Financial Engineers with in-depth product knowledge. You will be joining a rapidly expanding specialized area of Bloomberg focused on offering premium structuring, valuation and risk services to our client base.
The candidate should have recent experience at a Dealer (or at other top financial institutions) in financial engineering, structuring, and/or trading OTC Derivatives/Structured Notes. Familiarity in bespoke derivatives term sheets, the industry standard valuation models and "street practices" used for security valuation and portfolio risk analysis is imperative. Experience using Bloomberg, Numerix and other derivative pricing platforms is a plus.
Valuation will rely heavily on the appropriate choice and use of pricing models (combined with appropriate adjustments when necessary). Therefore the candidate must have sufficient understanding and intuitive skills to assess if model results are reasonable. Successful candidate with strong communication skills may engage in a "client facing" role. The candidates will be working with various people from external clients (traders, sales, buy side, institutional investors), and internal sales specialists, to developers and quants.
Essential requirements:
-Credit Derivatives, Credit Structured products and Structured Finance product and market risk experience is essential.
-Strong understanding of derivatives models including market conventions, vanilla/exotic options, and market practices regarding bespoke exotic valuation and hedging.
-Exceptional written and verbal communication skills. Proficiency with Excel and Word. Candidates must also have the ability to present in front of a group and interact with clients, via phone or face-to-face.
-Ability to work in a fast-paced, complex and cross-asset environment.
Qualifications:
-Master's degree in a technical area (such as Math, Physics or Engineering), quantitative finance related. Master Degrees (or DEA), PhD in mathematical finance.
-Working knowledge of Excel, VBA. Familiarity with financial libraries (C, C++) and mathematical .packages such as Matlab or Mathematica a plus.
-Ability to work with multiple groups across reporting lines.
-Minimum of 5 years of experience at a Dealer (or at other top financial institutions).
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 company¿s 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 315,000 subscribers globally. Bloomberg's enterprise solutions build on the company's 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 three magazines, Bloomberg Businessweek, Bloomberg Markets and Bloomberg Pursuits, covers the world with more than 2,400 news and multimedia professionals at more than 150 bureaus in 73 countries. Headquartered in New York, Bloomberg employs more than 15,000 people in 192 locations around the world.
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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