Quant Researcher - Monetization

A team at a leading $20Bn+ global hedge fund is seeking a Quantitative Researcher to join a high-performing systematic trading group focused on alpha monetisation and portfolio optimisation.

The team is open to candidates from a range of systematic backgrounds, including equities, futures, macro, multi-asset, or statistical arbitrage, provided they have demonstrated experience improving signal monetisation, portfolio construction, execution, or risk-adjusted returns.

The hedge fund provides world-class technology, data, and research infrastructure, enabling researchers to focus on generating alpha and efficiently scaling strategies into production.

Responsibilities

• Conduct research focused on improving monetisation of systematic trading signals.
• Develop portfolio construction, capital allocation, and risk management frameworks to maximise risk-adjusted returns.
• Analyse signal interactions, capacity constraints, turnover, transaction costs, and execution dynamics.
• Collaborate closely with Portfolio Managers, Quantitative Researchers, and Technology teams to deploy strategies into production.
• Contribute to the ongoing enhancement of research infrastructure, modelling frameworks, and portfolio analytics.

Requirements

• 2-10 years of experience in quantitative research at a hedge fund, proprietary trading firm, asset manager, or systematic investment team.
• Demonstrated experience monetising alpha signals through portfolio construction, optimisation, execution, or risk modelling.
• Strong understanding of systematic investment processes and the drivers of strategy performance.
• Advanced degree in Mathematics, Physics, Statistics, Computer Science, Engineering, Economics, or a related quantitative discipline.
• Strong programming skills in Python and experience working with large financial datasets.
• Excellent analytical and problem-solving skills with the ability to operate in a collaborative, fast-paced environment.

If interested, please apply via the link. Due to the high volume of applications, additional time may be needed for suitable applicants to receive a response.