Linear Rates Quant - London, United Kingdom - eFinancialCareers

eFinancialCareers

Verified Company

London, United Kingdom

5 days ago

Posted by:

Tom O´Connor

beBee Recruiter

Description

Bloomberg's Quantitative Analytics team is responsible for the design and implementation of modelling 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, includingmarket 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 deliverythrough a modern C++ library.

Within the Quantitative Analytics team, the Greeks Analytics group is responsible for developing efficient solutions for vanilla and exotic derivative portfolio sensitivity calculations, as well as deploying these into production in cooperation with our ModelValidation, Engineering and Product Manager partners.

Typical responsibilities will include:

Industrial-strength implementation of a multi-curve framework and linear IRD pricing:

Design and implement a modern post-Libor multi-curve construction engine with native Algorithmic Differentiation (AD) support
Contribute to the design and extension of our derivative portfolio sensitivity calculation framework, focusing on AD based interest rate sensitivities
Design and extend the public APIs for interest rate curve construction and sensitivity calculations
Write modern, clean, reusable, well tested, peerreviewed C++ code
Improve the performance of derivative portfolio workflows, to reduce hardware costs

Product management:

Translate business requirements into precise math that translates well into algorithms
Handle workflows and requirements from sell

- and buy-side clients, both for trading and regulatory purposes

Provide mathematical and technical documentation to internal stakeholders and external clients
Keep up to date with mathematical, technical and regulatory innovation in the financial industry

Stakeholder relationship management:

Work closely with quants and quant developers to quickly iterate design and modelling decisions
Liaise with business stakeholders: discuss and finalise specs, solve project issues
Support our clients and Sales team
Work closely with our Engineering department to integrate quant code into IT systems
Discuss functionality and tests with Model Validation for release to production

You'll need to have:

A Masters or PhD level qualification from a leading university in a quantitative discipline (such as Mathematics, Physics, Engineering or Quantitative Finance).
Significant experience (VP level or above) from a leading buy or sellside institution developing, implementing, and delivering linear interest rates data, pricing and sensitivity analytics. Experience of Algorithmic Differentiation is useful.
Proficient in modern C++ software design and implementation. Familiarity with Python is useful, but not essential.
Good communication and writing skills and ability to interact productively and positively with multiple stakeholder teams, both internally and with external clients in support of our Sales teams.

Why Bloomberg?
Bloomberg is committed to diversity. It drives our innovation. At Bloomberg, you'll have the opportunity to go above and beyond and to take risks. You'll be a part of an organization that is entering new markets, launching new ventures, and pushing boundaries.

Our ever-expanding array of technology, data, news, and media services fosters innovation and empowers clients and offers nearly limitless opportunities for career growth.

If this sounds like you:
Bloomberg is an equal opportunity employer and we value diversity at our company.

We do not discriminate on the basis of age, ancestry, colour, 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 maternity/parental leave, protected veteran status, status as a victim of domestic violence,or any other classification protected by applicable law.