Senior Quantitative Engineer - Fixed Income - Artificial Intelligence

Overview

On Site
USD 165,000.00 - 260,000.00 per year
Full Time

Skills

Artificial Intelligence
Stacks Blockchain
Securities
FOCUS
Writing
Cloud Computing
Modeling
Credit Risk
Fixed Income
Pricing
Bloomberg
Documentation
Statistical Models
Finance
Valuation
Research
Mathematics
Statistics
Machine Learning (ML)
Software Engineering
Computer Science
Data Structure
Algorithms
Communication
Collaboration
Publications
Training
Life Insurance

Job Details

Description & Requirements

Bloomberg's Engineering AI department has 350+ AI practitioners building highly sought after products and features that shape global markets. In our fast-paced fixed income domain, you'll design and implement advanced models that leverages modern ML and statistical techniques on top of novel technology stacks and vast data sources to price accurately millions of securities. We are heavily invested in data-driven solutions that combine statistical and machine learning solutions to price diverse asset classes, with a strong focus on Fixed Income. Building on the success of modern ML-based pricing solutions such as IBVAL, we are expanding our group to tackle more ambitious challenges in fixed income modeling. In this role, you will contribute novel modeling ideas and bring them to life by writing clean, modular, production-quality code for cloud-native environments, ensuring your work makes a tangible impact.

We seek highly multifaceted skilled individuals with expertise in Fixed Income modeling, interest rate theory, credit risk, or advanced statistical/machine learning techniques to join our team.

You'll have the opportunity to:

  • Develop, build and evaluate statistical and Machine Learning models that directly influence how global markets price fixed income assets.
  • Collaborate with cross-functional teams to develop, test, monitor and maintain robust production systems.
  • Design new architectures, systems and approaches to power the pricing capabilities of Bloomberg.
  • Integrate cutting-edge academic and industry research into models and methodologies, staying ahead of emerging developments to drive continuous innovations.
  • Represent Bloomberg at scientific and industry conferences, and publish research findings through documentation, whitepapers, or in leading academic journals and conferences.

You'll need to have:

  • 3+ years of relevant work experience with Machine Learning or Statistical Modeling techniques in the financial industry ideally around asset valuation.
  • Ph.D. or M.Sc. with equivalent research experience in Machine Learning, Computer Science, Mathematics, Statistics or a related field.
  • Thriving in solving challenging, often ill-defined problems where off-the-shelf solutions fall short, and bring a creative, rigorous approach to developing novel methods and technologies.
  • Proven track record designing, building, evaluating and maintaining statistical or Machine Learning solutions on Production.
  • Proficiency in software engineering with an understanding of Computer Science fundamentals such as data structures and algorithms.
  • Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders.
  • A track record of authoring publications in top conferences and journals is a strong plus

Salary Range = 00 USD Annually + Benefits + Bonus

The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.

We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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