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Selby Jennings invites a visionary Head of Machine Learning to shape the ML strategy of a leading hedge fund. You will define the research agenda, recruit top talent and set the direction for scalable ML across systematic investing and markets.
You will lead a high-calibre team, drive breakthrough methods in deep learning, RL, probabilistic modelling and time-series, and partner withInvestment teams to translate research into deployed, high-impact trading capabilities.
We are seeking an exceptional Head of Machine Learning to build and lead the ML capability within a leading hedge fund.
This is a senior, high-impact role responsible for defining the firm's machine learning strategy, building a world-class research team, and applying cutting-edge ML techniques to complex problems across systematic investing and financial markets.
We are open to outstanding individuals from hedge funds, investment banks, quantitative trading firms, leading technology companies and AI research organisations. Prior financial markets experience is advantageous but not essential for candidates with exceptional ML expertise.
We are seeking an exceptional Head of Machine Learning to build and lead the ML capability within a leading hedge fund.
This is a senior, high-impact role responsible for defining the firm's machine learning strategy, building a world-class research team, and applying cutting-edge ML techniques to complex problems across systematic investing and financial markets.
We are open to outstanding individuals from hedge funds, investment banks, quantitative trading firms, leading technology companies and AI research organisations. Prior financial markets experience is advantageous but not essential for candidates with exceptional ML expertise.
The successful individual will bring:
Candidates could come from:
For candidates from finance, experience applying ML to systematic investing, quantitative research or trading would be particularly relevant.
For candidates coming from technology or AI research, previous financial experience is not essential where there is exceptional technical depth and an interest in applying ML to challenging quantitative problems.
A strong academic background in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering or a related quantitative discipline is preferred. A PhD is highly desirable but not essential.
Relevant expertise may include:
This is an opportunity to shape and build a machine learning function with significant strategic ownership. The successful candidate will have the resources and autonomy to hire exceptional talent, pursue ambitious research and directly influence how advanced ML is used across systematic investing.