Quantitative Developer - Systematic

About the role

About Man Group

Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and advanced technology, our single and multi-manager investment strategies are underpinned by deep research and span public and private markets, across all major asset classes, with a significant focus on alternatives. Man Group takes a partnership approach to working with clients, establishing deep connections and creating tailored solutions to meet their investment goals and those of the millions of retirees and savers they represent.

Headquartered in London, we manage $253.6 billion* and operate across multiple offices globally. Man Group plc is listed on the London Stock Exchange under the ticker EMG.LN and is a constituent of the FTSE 250 Index. Further information can be found at www.man.com

At Man Group, we respect your privacy and we are committed to protecting and safeguarding your Personal Data. We have developed policies and processes which are designed to provide for the security and integrity of your Personal Data. We are committed to Processing your Personal Data fairly and lawfully, and being open and transparent about such Processing. For further information on how we process your data, please see the privacy notice for applicants here.

* As at 30 June 2026

The Role

We're setting up a new engineering team in Shanghai, working hand-in-hand with Portfolio Managers to develop and deploy new systematic trading strategies. As a Software Engineer in the Front-Office Engineering organization, your code will have a direct line of sight to live markets.

Your work will span the full lifecycle of strategy development: onboarding new datasets, implementing trading signals, building portfolio optimization tools, developing data visualization frameworks, and enhancing our research platform. You'll solve performance-critical problems using efficient numerical algorithms and cluster-computing solutions.

This is a chance to get in early and do engineering work that visibly moves the needle.

Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: NumPy, SciPy, Pandas, statsmodels, and scikit-learn to name a few of the libraries we use extensively. For storage, we rely heavily on MongoDB and MS SQL.

We use Control-M and Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, Docker for containerisation, Ansible for architecture automation, and Slack for internal communication. Our technology list is never static: we constantly evaluate new tools and libraries.

Key Competencies

Essential

- Minimum of 2 years of professional experience in software engineering, preferably with a focus on quantitative applications