Rates Trading Strategies - Quantitative Trader - Associate or Vice President

JPMorgan Chase & Co.
London
2 months ago
Create job alert

The team is tasked with researching and delivering systematic, quantitative trading strategies, while maintaining correct risk and maximizing returns.

Job summary


As an Associate or Vice President within the Rates Trading Strategies team, you will research, develop, test, and implement quantitative trading strategies, with a focus on risk management and return maximization on linear Interest Rates products (Government Bonds, IR Swaps).


You will be responsible for collaborating with Quantitative Research, Voice Trading and Technology to deliver these strategies to production, and with the wider team to integrate them within a portfolio of strategies, in a fast-paced, results-orientated environment.


Job Responsibilities

Conduct in-depth research of systematic alpha opportunities Develop and implement quantitative trading models, algorithms, and strategies Back-test and optimize trading strategies using rigorous analysis Originate innovative trading strategies in collaboration with the voice trading desks Collaborate with the technology teams to build and maintain robust trading systems Deliver an end-to-end product, from the idea to real-time trading

Required qualifications, capabilities, and skills

You have an advanced degree (or equivalent) in mathematics, statistics, or computer science. You demonstrate strong programming skills in Python, Java, or similar languages. You have hands-on experience processing with large tick datasets and research at scale. You demonstrate in-depth knowledge of statistical modelling and inference, machine learning, and optimization techniques. You have proven experience in quantitative trading with a demonstrable track record. You have an excellent problem-solving and analytical skills. You have ability to work independently and as part of a team.

Preferred qualifications, capabilities, and skills 

You have experience with high-frequency trading, electronic trading or algorithmic trading. You demonstrate knowledge of database systems (KDB, SQL) You have outstanding communication skills You have experience working collaboratively on common codebases using git

This role encompasses the performance of UK regulated activity. The successful candidate will therefore be subject to meeting UK regulatory requirements in the assessment of fitness, propriety, knowledge and competence (as assessed by the Firm) and (where appropriate) approval by the UK Financial Conduct Authority and/or the Prudential Regulation Authority to carry out such activities.

Related Jobs

View all jobs

Quantitative Portfolio Manager (London Area)

Quantitative Developer - Crypto

Quantitative Portfolio Manager

Quantitative Researcher - Systematic Rates

Quantitative Researcher - Systematic Rates (London Area)

Website Trading Manager

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.