At a Glance
- Tasks: Identify structural alpha and design AI research pipelines for trading strategies.
- Company: Dynamic hedge fund in London with a focus on systematic trading.
- Benefits: Competitive salary, performance-based bonuses, and growth opportunities.
- Other info: Join an early-stage team where your contributions are directly rewarded.
- Why this job: Make a real impact in a cutting-edge AI-native research environment.
- Qualifications: 3-10 years in quantitative research with strong Python skills.
We are partnering with a London-based systematic hedge fund, currently launching with approximately $500M AUM in secured commitments, to place two quantitative researchers across short-term systematic macro and short-term equities. The firm runs a shared book with clean PnL attribution per strategy rather than individual books. Research output feeds directly into capital allocation. This is a production-oriented research role with clear performance-based payout mechanics tied to strategy contribution.
What You Will Solve
- Structural alpha identification: Given that the firm runs hundreds of live strategies across macro, FX, equity and commodity futures, how do you isolate genuinely uncorrelated structural inefficiencies in your domain rather than recombining existing factor exposure?
- AI system architecture: How do you design and manage multi-agent research pipelines, including context engineering, model selection per task, memory systems, and output validation, at a level that materially accelerates research throughput?
- Regime-robust execution: How do you construct strategy-level sizing and execution frameworks that account for slippage, market impact, and cost structure across futures and FX venues under varying liquidity conditions?
Structural Edge
- Direct strategy-to-capital-allocation pipeline with full PnL attribution
- Investor mandate supporting AUM growth toward $1B+, providing scalable capital for high-conviction strategies
- Early-stage team where individual research contribution is visible and directly rewarded
- AI-native research environment operating beyond code generation
Ideal Profile
- The Key Metrics: 3 to 10 years in a systematic research or quant trading role at a hedge fund, prop firm, or bank QIS desk. Sharpe above 1.5 in futures. PnL numbers secondary to understanding of why edge exists and why it persists.
- The Tech: Python at production level. Demonstrated experience building or operating AI agent systems for research automation.
Compensation & Preferences
- Non-compete: Preference for candidates with fewer than 12 months remaining. Candidates with immediate availability are prioritised.
- Compensation: £120,000 base + performance-based payout tied to attributed strategy PnL. Bonus potential £300,000 to £500,000+ in line with personal plus fund performance. This is not a guarantee of compensation or salary; a final offer amount may vary based on factors including but not limited to experience, domain expertise, and geographic location.
Quantitative Researcher / Systematic Futures & FX | London employer: Onyx Alpha Partners
Onyx Alpha Partners is an exceptional employer, offering a dynamic and collaborative work culture in the heart of London. With a strong focus on employee growth and development, we provide our team members with unique opportunities to excel in systematic trading strategies while leveraging cutting-edge technology. Join us to be part of a forward-thinking firm that values innovation and teamwork, ensuring a rewarding career path in the fast-paced world of macro and commodity trading.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher / Systematic Futures & FX | London
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We think you need these skills to ace Quantitative Researcher / Systematic Futures & FX | London
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