Applied Research Opportunities at Man AHL (Oxford, UK)

[Slavi Marinov]

At AHL we mix mathematics, computer science, statistics and engineering with terabytes of data to understand and predict financial markets. We are led by research and technology, building models and writing programs that invest billions of dollars every day. We are a small flat-structured company with a no-attitude feel, and you will have plenty of opportunity to grow and have enormous impact on what we do. You will help to build the trading systems of the future by discovering and modelling predictable structure in vast collections of financial market and related data.

Building on AHL's existing successes in machine learning and its significant ongoing initiatives in data capture, archive and retrieval, exciting opportunities have arisen in the development of self-organised trade, execution and risk models that harness vast amounts of input data of different types from a diversity of sources. Additional applications include the identification, dynamic monitoring and capture of web-based public and private data, anomaly detection and the identification of change-points and regimes. Previous experience of modelling financial market data is an advantage but not a prerequisite.

Successful Research Analyst candidates will have:

* A doctorate and substantial research experience in an area of computational statistics, machine learning, computational linguistics or natural language processing
* Practical "hands-on" experience of
* capturing, cleaning and modelling empirical data in an applied environment
* extracting and combining numerical, categorical and text-based information
* modern techniques in machine learning, signal processing and forecasting
* A passion for understanding financial markets through empirical data analysis and modelling
* Excellent programming, scripting and scientific computing skills in Python & Linux
* Broad expertise, pragmatism and open-mindedness
* Excellent communication skills and enjoyment of collaborating to solve practical problems

As well as working closely with Man AHL's researchers and investment professionals in London, Switzerland, Hong-Kong and Australia, these positions also offer unique opportunities for interacting with the academic activities of the Oxford-Man Institute of Quantitative Finance and its collaborating departments within the University of Oxford.

Feel free to ping me if interested: smar...@ahl.com. See you all at NIPS!

Slavi