Introducing Man AHL Technology

Technology is at the heart of everything we do at Man AHL. State-of-the-art quantitative trading strategies necessitate state-of-the-art technology at all stages; from market data acquisition and initial research through to model implementation and trade execution.

Who we are

We are a group of over 60 software technologists with varied backgrounds including computer science, mathematics, physics, engineering and classics.

Our team includes astrophysicists, musicians, and a Kendo champion. We speak over 10 languages. What unifies us is a passion for writing high-quality code.

Our developers are organised into small cross-functional teams. Our engineering roles cover a spectrum from developing our platform and core technology (“Core System Developers” or “Trading Systems Developers”) through to using the platform and working with our Quant Researchers to develop trading models (“Quant Developers”). People often rotate teams in order to learn more about our system, as well as find the role that best matches their interests.




How we work

Man AHL’s engineering culture is open and collaborative: we try to help and learn from one another. We have a flat hierarchy with a `no-attitude` feel, where discussions are always about ideas and never about titles.

We hold monthly internal seminars, bi-annual “FedEx days” (where we take projects we’re passionate about from idea to completion in 24 hours). All technologists are encouraged to attend the major conferences on the topics they are passionate about, be it databases, programming languages, DevOps, OSS, or machine learning.

We don’t believe in any barrier between technology and the wider business. As such, technologists have opportunities to learn and contribute to all parts of the business. We have regular internal courses and seminars on research and finance topics. Technologists at Man AHL have researched, back tested and implemented profitable trading models.

Technologies we use

All of our production systems use Linux. We are heavy users of Python and its full scientific stack including numpy, scipy, pandas and scikit-learn.

While most of our codebase is written in pure Python, when we push the performance boundaries of Python we use Cython/C/C++ as required. We implement the systems that need the highest data throughput in Java.

Some other tools we use:

Apache Kafka  Airflow  Apache Spark  Jenkins  Grafana  Theano  Prometheus  Arctic  PyBlogs 

Working with others

At Man AHL we have benefited hugely from open-source technologies. We contribute back to the community whenever we can.

  • We have open-sourced Arctic, the time series storage engine that powers all of our internal time series data; as well as PyBloqs, a project we use heavily for internal reporting
  • As heavy users of Python and its scientific stack, we sponsor and host the Pydata meet up: London’s biggest monthly event for data scientists using Python
  • We attend and sponsor major scientific and programming conferences, including ICML, NIPS, and PyData London
  • Given that maths and code drive everything we do, we support maths and programming education and we sponsor the UK team at the European Girls’ Mathematical Olympiad


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