National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Quantitative Developer - C++ Infrastructure for Quant Analytics

eFinancialCareers
Greater London
3 weeks ago
Create job alert

Quantitative Developer - C++ Infrastructure for Quant Analytics

Location
London

Business Area
Product

Ref #
10043631

Description & Requirements

The Quant Analytics department at Bloomberg sits within Enterprise Products and is responsible for modeling market data, pricing, and risk calculations of financial derivatives across all asset classes. Our C++ libraries are used by all Bloomberg products and services, including the Terminal with over 300,000 clients, trading system solutions, enterprise risk management, and derivatives valuation services.

The department includes several Quant teams focused on different asset classes, as well as portfolio-level analytics and model validation. These teams deliver C++ libraries, supported by Python-based validation and testing, that are integrated by the Engineering department into Bloomberg's IT systems.

The Quant Library Architecture (QLA) team offers the opportunity to build experience at the cutting edge of C++ and financial mathematics, engaging with and influencing a wide variety of stakeholders of differing skill sets, to deliver scalable and strategic enterprise pricing and risk solutions. QLA is a small team of C++ experts tasked with helping the Quants be as productive as possible, for the long term. We are seeking a proficient C++ developer, with a strong interest in modern software development life-cycle practices.

We'll trust you to:

Support Quants; owning the developer experience for Quants. We build and debug C++ libraries either in VS Code remote containers in Docker, or directly on Unix hosts. Much of the infrastructure is provided by Engineering, but QLA maintain significant additional tooling to provide Quants the most powerful and usable development environment possible. Proactively maintain integration builds and test infrastructure. We run largely automated CI/CD builds with a wide variety of static analysis and other code quality assurance tooling. This affords not just ongoing regression testing, but also early warning of issues that might impair Quants' development environment. Rapid response and ongoing improvements to these systems are a key responsibility. Oversee architecture. Quants own a reasonable number of libraries interfaced into a wide variety of systems. QLA are heavily involved in API design and library architecture to meet Engineering standards whilst optimizing time to delivery, performance, and robustness. We also assess and provision 3rd party software when proven superior. Review code. Assisting Quants with coding best practices and improved solutions both when requested and proactively when appropriate. Once those Keep-The-Lights-On responsibilities are met, continue with project work as prioritized in partnership with Quants. This might be longer term improvements related to the above, development work on infrastructuralponents (such as the interfacing and orchestration library layers), performance tuning, or deeper engagement with Quant projects. Proactively engage stakeholders from a variety of backgrounds. Understand, document andmunicate sometimes quiteplex requirements. Context switch between strategic projects and urgent support requests. Clearly and conciselymunicate a strategy, adaptingmunication to suit the audience and their concerns.


You'll need to have:
7+ years of full software development life-cycle experience. Demonstrable proficiency with C++. Experience designing effective APIs. Knowledge of Python or other scripting languages.
Knowledge of financial products such as derivatives, interest rates, or equity markets.
We'd love to see:
Experience mentoring and coaching other team members. Technical experience in some of CMake, AAD, Linux, Unix (Sun/IBM), Docker, WSL, Python, or OCaml. Knowledge of financial mathematics such as optimization techniques, monte-carlo, etc. A keen interest in developing skills in these areas.
Job ID 3171_10043631

Related Jobs

View all jobs

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

National AI Awards 2025

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.

How to Get a Better Data Science Job After a Lay-Off or Redundancy

Redundancy can be tough to face, especially in a competitive field like data science. But it’s important to know: your experience, analytical thinking, and modelling skills are still in demand. Across sectors like healthcare, finance, e-commerce, government and AI startups, UK employers continue to seek data scientists who can deliver value through insight, prediction, and automation. This guide will walk you through how to bounce back from redundancy with purpose and clarity—whether you're a data analyst looking to step up, a mid-level data scientist, or a machine learning specialist seeking a better-aligned opportunity.

Data Science Jobs Salary Calculator 2025: Find Out What You Should Earn in the UK

Why last year’s pay survey is already out of date for UK data scientists “Am I being paid enough?” Every data professional eventually asks that question—often after a teammate reveals a hefty counter‑offer, a recruiter shares a six‑figure opening, or a headline trumpets the latest multimillion‑pound AI investment. Yet salary guides published even twelve months ago belong in a museum. Generative‑AI hype re‑priced Machine‑Learning Engineer roles, LLM fine‑tuning turned Prompt Engineering into a genuine career path, & fresh regulation forced companies to hire Responsible‑AI Officers on senior‑scientist money. To cut through the noise, DataScience‑Jobs.co.uk distilled a transparent, three‑factor formula. Insert your role, your region, & your seniority, and you’ll get a realistic 2025 salary benchmark—no stale averages, no vague ranges. This article walks you through the formula, examines the forces pushing data‑science pay ever higher, and offers five concrete actions to boost your market value within ninety days.

How to Present Data Science Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

The ability to communicate clearly is now just as important as knowing how to build a predictive model or fine-tune a neural network. In fact, many UK data science job interviews are now designed to test your ability to explain your work to non-technical audiences—not just your technical competence. Whether you’re applying for your first data science role or moving into a lead or consultancy position, this guide will show you how to structure your presentation, simplify technical content, design effective visuals, and confidently answer stakeholder questions.