Technology-empowered, diversified active investment management focused on delivering performance and client portfolio solutions.

Built for the modern Python data science ecosystem, ArcticDB lets you handle complex real-world data quickly and at petabyte scale. James Munro and Abhi Thakur take you behind the scenes.

A look at providing spaces at the office for electronics, music and other creative hobbies.

Combining data science and expert human overlays can help you better judge a company’s ESG credentials.

With the release of the latest version of Man Group’s ‘Notebooker’ project, users can now set up their Jupyter Notebooks to be run as reports on a schedule.

Custom reports from Python code or notebooks can be time-consuming - PyBloqs can simplify the process.

CLAs have benefits, but they can cause friction. At Man, we've found the drawbacks can be largely solved through standardised CLAs (or by not using one at all).

How you can start using Arctic for highly intuitive data storage and retrieval.

Moore's Law is broken - that's why we built our own cloud.

In this article, five of our summer interns tell us about their time at Man Alpha Technology, what they’ve learned, and the opportunities they experienced.

How our work with Dapr and the open-source community is helping us deliver a cloud-native vision across a diverse technological landscape.

Building a scalable data repository and reporting framework to provide RI insights that support investment decision making, client reporting and risk management.

Re-platforming and migrating Man Numeric from SAS to Python.

Real-time, interactive, auto-plotting charts on JupyterLab. Read about our newly open-sourced add on!

Our journey adopting Aeron messaging to improve the latency of our FX execution system, thus reducing trading slippage for our clients.

Understanding an organically grown application landscape and modelling criticality based on different views of application and data risk.

Man Group's newly open-sourced project, Notebooker, empowers users to publish their work with a few simple clicks.

With PartialTesting, we can speed up build-times and reduce compute requirements – run the tests that matter, ignore those that don’t!

How Man Group's Technology teams enabled the firm to thrive remotely.

Man Group recently open sourced their own, internally designed feedback tool - Adaero. Here’s why …

We've recently open-sourced another tool, called D-Tale (a.k.a. ‘the details of your data’).

Financial markets are now being swayed not only by numbers, but also by words. How can automatic analysis of text by computers, also known as Natural Language Processing, predict financial movements?

Open Source licensing is mainstream today and for modern data science libraries it has become practically the default.

Open sourcing a new database tool.

Here’s how we use the Prometheus time-series database for insight into our systems.

Managing OpenStack Virtual Machines to improve user experience, avoid capacity constraints and maximise hardware performance.

AHL Tech Article 'Capturing System Core Dumps'.

A clear leading dataframe implementation in JavaScript has not emerged. This article gives a review of a selection of the current options and poses the question - “what would an ideal JavaScript dataframe look like?”.

How we centralized and simplified the capture of core dumps in Docker using common Linux tools.

How do you perform logging in software that represents a large mathematical model? If the model isn't behaving as expected, is it the code or the data that's at fault?

At AHL, automated testing is a key tool to help us produce high quality code. For our Python based tests we rely heavily on Pytest. In this article we look at why we chose Pytest and how we use it.

I have been fortunate to have spent three months as an intern at Man AHL, a quantitative investment manager. Man AHL is well known for its creativity, innovation and technical prowess – but what is it like for an intern?

Despite a reputation for fast change some technology choices have stayed remarkably static over the past few decades.

At Man AHL, we use Python for almost everything. We build models in Python, support trading systems in Python, and write web visualisation tools in Python.