Senior ML Quant Engineer - Fixed Income - Artificial Intelligence

Bloomberg; Greater London; On-site; GBP 80,000 - 110,000; Full time

Job summary

Bloomberg is looking for a Senior ML Quant Engineer in London to design and evaluate Machine Learning models for financial asset pricing. The role involves collaboration with cross-functional teams and requires a strong foundation in statistics and programming. Ideal candidates will have a Ph.D. or M.Sc. in a related field and experience in the financial sector. The position emphasizes innovation and a track record of publications in academic circles. Join Bloomberg in advancing AI capabilities in finance.

Qualifications

• Previous work experience with Machine Learning or Statistical Modeling in finance.
• Proficiency in software engineering and understanding of data structures.
• Ability to solve challenging problems and create novel methods.

Responsibilities

• Design, build and evaluate statistical and ML models for pricing fixed income assets.
• Collaborate with cross-functional teams for robust production systems.
• Represent Bloomberg at conferences and publish research findings.

Skills

Machine Learning

Statistical Modeling

Communication skills

Software engineering

Fixed Income modeling

Interest rate theory

Education

Ph.D. or M.Sc. in a relevant field

Job description

Senior ML Quant Engineer - Fixed Income - Artificial Intelligence

Location: London

Business Area: Engineering and CTO

Ref #: 10049296

Description & Requirements

Bloomberg’s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.

At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.

Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.

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

You’ll Have The Opportunity To

• Design, 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 tools to power next-generation pricing capabilities of Bloomberg.
• Integrate cutting-edge academic and industry research into models and methodologies, staying ahead of emerging developments to drive continuous innovation.
• 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

• Previous relevant work experience with Machine Learning or Statistical Modeling techniques in the financial industry, ideally around asset valuation. A track record designing, building, evaluating, and maintaining statistical or Machine Learning solutions in production is a plus.
• 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.
• 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.

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.