Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Quantitative Engineer - Fixed Income - Artificial Intelligence

Bloomberg
London
4 days ago
Create job alert

Senior Quantitative Engineer - Fixed Income - Artificial Intelligence

Location
London

Business Area
Engineering and CTO

Ref #
10045475

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 leverage modern ML and statistical techniques on top of novel technology stacks and vast data sources to accurately price 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.

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.


Bloomberg provides reasonable adjustment/accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job or to perform your job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you would prefer to discuss this confidentially, please email (Europe, the Middle East and Africa). Alternatively, you can get support from our disability partner EmployAbility, please contact +44 7852 764 684 or

Related Jobs

View all jobs

Senior Quantitative Engineer

Senior Quantitative Engineer - Fixed Income - Artificial Intelligence

Senior Quantitative Engineer - Fixed Income - Artificial Intelligence

Senior Quantitative Finance Analyst

Senior Quantitative Finance Analyst

Senior Quantitative Finance Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.