Technology at Man

Discover how our approach to data science and tech innovation is powering investment performance.

Performance powered by technology

Technology is the cornerstone of everything we do at Man, driving investment research, decision-making, execution, and reporting. 

We never stand still, continuously investing in data sources, infrastructure, machine learning models and talent to push the boundaries of what’s possible.  

Staying at the forefront of technological advancements is our edge. From open source leadership to proprietary innovations, Man’s tech platform enables efficiency, insight and transparency at scale. 

At Man, every colleague across the business is empowered to seek out new opportunities and advance our platform to deliver better outcomes for clients.

600+

Technologists and Quants

200+

New datasets added in 2025

$7.5 trillion

Notional trading volume

Python

Second most-used language at Man after English

Statistics as at 31 December 2025.

Gary Collier

"At Man, we view technology as a core competitive advantage, enabling us to innovate, adapt and deliver for our clients. We deliver this through exceptional people building exceptional technology platforms, which can handle scale, complexity and customisation."

Gary Collier Chief Technology Officer, Man Group

Inquisitive minds wanted

Our tech team tackles complex challenges head-on, building scalable solutions and crafting transformative tools that shape the future of investment management. It’s a place where creativity thrives on collaboration, and diverse perspectives spark bold new ideas.

A commitment to the open source community

At Man, open source leadership is about more than code. Our commitment to the community shows how we're fostering a culture of creativity, connection and positive impact. We believe that creating and contributing to open source libraries means that we can help build the data science tools of the future.

Our dataframe database ArcticDB is one such example. Beginning as an open source project over a decade ago, it is now available as an enterprise solution to help quants handle billions of rows of data in a matter of seconds, all while seamlessly integrating with common Python data science libraries.

kafka
airflow
spark
jenkins
grafana
tensor-flow
prometheus
arcticdb
pybloqs

Investment involves risk, including potential loss of principal. Past performance does not guarantee future results.