Portfolio Manager

A rapidly growing, AI-native quantitative investment firm is building out its investment team ahead of launch. The firm brings together leading quantitative researchers, mathematicians, physicists and AI talent across the US, Europe and the Middle East.

The firm is now looking for mid/senior-level Quantitative Researchers or Portfolio Managers with a proven track record in mid-frequency trading (MFT). The ideal candidate will have 3–10 years of industry experience, with a preference for individuals coming from proprietary trading environments or entrepreneurial quant teams, rather than large, highly structured institutions. The opportunity is particularly suited to someone who wants to help build a platform and have meaningful ownership over research, strategy development and ultimately PnL.

About the Role

Responsibilities

• Help build a platform and have meaningful ownership over research, strategy development and ultimately PnL.
• Influence strategy development, research direction and the evolution of the trading platform.
• Work within a platform approaching launch with infrastructure, research stack and datasets already largely in place.
• Collaborate with a team of leading quantitative researchers, mathematicians, physicists and AI talent across the US, Europe and the Middle East.
• Work from the office with a minimum expectation of 3 days per week.

Qualifications

• Typically 3–10 years' experience in quantitative trading/research.

Required Skills

• Strong MFT experience, specifically in one or more of:
• Intraday futures
• Long/short strategies with typical holding periods of ~3–5 days
• ADR / global equity arbitrage
• Strong understanding of market microstructure and execution.
• Experience taking strategies from research through to live trading.
• Ideally, a demonstrable live PnL track record from strategies recently built or co-built.
• A genuine appetite to join an early-stage platform and help build something rather than simply inherit an established book.

Preferred Skills

• HFT experience is useful but not essential.