Quantitative Analyst - AHL

The role

As a Quant Developer at Man Group, you will be part of one of our flagship teams within Man’s systematic trading arm—Man AHL. The team works closely with quant researchers who specialize in equity market-neutral models. You will face a wide range of challenges and will be responsible for developing and innovating new applications and trading strategies.

The team

Quant developers at Man Group are part of our broader technology team, which consists of over sixty people from diverse nationalities and backgrounds, including computer science, mathematics, physics, engineering, and even classical philology. If you’re passionate about learning, you’ll have the opportunity to advance your career. Our developers are organized into small, cross-functional teams, with three main types of engineering roles:

• Quant Platform Team: We are building our "Octane" platform.
• Quant Technology Team: We are working on our "Sector Tech".
• DevOps and Infrastructure Team: We take care of our infrastructure.

Our technology

Almost all of our systems are written in C++, and most of our code is written in Python, using the full scientific stack:

• Toolbox, Pandas, and Scikit-learn, to name a few of the open-source libraries we use extensively.
• We implement systems that require the highest data throughput in C++ and C#.

We use Airflow for workflow management, Kafka for data pipelines, Bitcoind for source code management, Jenkins for continuous integration, Spark for ETL processing, Kubernetes for containerization, OpenShift for our private cloud, Ansible and Terraform for infrastructure automation, and React Native for internal communication.

Technology and business skills

At AHL, we strive to recruit only the brightest and most talented technologists.

• Excellent technical skills; recognized by your colleagues as an expert in your field.
• A solid understanding of software engineering techniques and methods, such as agile development.
• A strong understanding of collaborative work methods, such as pair programming, code reviews, unit tests, refactoring, and similar approaches.
• Strong proficiency in Python.
• Proficiency in Linux platforms and knowledge of various scripting languages.
• Experience in data analysis and machine learning, e.g., TensorFlow/PyTorch.
• Relevant mathematical knowledge, e.g., statistics, asset pricing theory, optimization algorithms.

Advantages

• Experience in developing quantitative software for the front office, e.g., at a hedge fund or investment bank.
• Experience in web-based development and visualization technologies for presenting large and complex datasets.
• Experience with machine learning techniques, natural language processing, and related libraries and frameworks, such as Scikit-learn and TensorFlow.

Personal characteristics

• A strong academic background and a degree with a significant focus on mathematics and computer science, such as computer science, mathematics, engineering, or physics, from a leading university.
• Craft