Quantitative Developer, Systematic Equities

Millennium Management LLC

London

5 months ago

Applications closed

Related Jobs

View all jobs

Quantitative Researcher with Machine Learning experience, Systematic Equities

Principal Machine Learning Scientist - Time Series Expert

Market Data Engineer.

AHL Investment and Data Analyst Apprentice London

Quant Developer/ Data Engineer

Treasury Quantitative Developer - Data Engineer (London)

Job Description: Quantitative Developer, Systematic Equities

Please send resume submissions to and referenceREQ-19460in the subject line.

Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.

A small, collaborative, and entrepreneurial systematic investment team is seeking an experienced developer to join in building critical trading infrastructure. This opportunity provides a dynamic and fast-paced environment with excellent opportunities for career growth.

Location: London

Principal Responsibilities

Partner closely with the Portfolio Manager to develop data engineering and prediction tools primarily for the systematic trading of equities.
Develop software engineering solutions for quantitative research and trading
- Assist in designing, coding, and maintaining tools for the systematic trading infrastructure of the team.
- Build and maintain robust data pipelines and databases that ingest and transform large amounts of data.
- Develop processes that validate the integrity of the data.
Implementation and operation of systems to enable quantitative research (i.e., large scale computation and serialization frameworks)
- Live operation of such systems, including monitoring and pro-active detection of potential problems and intervention.
Stay current on state-of-the-art technologies and tools including technical libraries, computing environments, and academic research.
Collaborate with the PM and the trading group in a transparent environment, engaging with the whole investment process.

Preferred Technical Skills

Master’s or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field appropriate to a computational background.
Expert in C++.
Advanced programming skills in Python.
Strong Linux-based development.

Preferred Experience

Extremely strong computer science or engineering background with 3+ years of experience.
Approx. 3-4 years of professional experience in a computer science/computational role.
Experience working in a technical environment with DevOps functions (Google Cloud, Airflow, InfluxDB, Grafana).
Design and implementation of front-office systems for quant trading.

Highly Valued Relevant Experience

Knowledge of machine learning and statistical techniques and related libraries.
Experience as a quantitative developer supporting an intraday (or faster) system.
Experience with the development practices of large tech (Google/Meta, etc.) or finance firms.
Experience with financial data.

Target Start Date: As soon as possible

#J-18808-Ljbffr

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

Industry Insights

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

Jul 2, 2025

Careers

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

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Jun 29, 2025

Jobs

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Jun 24, 2025

Careers Jobs

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.