At a Glance
- Tasks: Create and optimise trading strategies using advanced statistical models and machine learning.
- Company: Leading quantitative HFT firm expanding into innovative mid-frequency strategies.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Exciting opportunity to work with cutting-edge technology and live trading environments.
- Why this job: Join a specialist team and make a real impact in the fast-paced world of finance.
- Qualifications: Strong background in statistical modelling, Python proficiency, and experience in portfolio construction.
The predicted salary is between 60000 - 80000 £ per year.
Company: A leading quantitative proprietary HFT firm expanding into mid-frequency strategies across global equities, futures, and derivatives markets.
Location: London
The role: The firm is building a specialist team focused on alpha blending, monetisation, and optimisation. The team works with a library of raw signals from the alpha research group to produce live, risk-bearing strategies, with exposure from signal combination up to execution.
Responsibilities
- Combine and weight a large set of raw alpha signals into coherent, tradable strategies, managing signal correlation, overlap, and interaction.
- Build and own the optimisation layer: portfolio construction, capital allocation, and position sizing across signals and markets.
- Model and minimise the cost of trading, accounting for market impact, transaction costs, and capacity constraints when translating signals into positions.
- Iterate on live performance: monitor PnL, diagnose alpha decay, rebalance signal weightings, and improve the capital efficiency of the book over time.
- Work with infrastructure and execution teams to deploy the combined strategies into production and refine them under live conditions.
- Own the live risk profile of the blended book, conducting rigorous risk assessment and managing exposures.
Requirements
- Strong background in statistical modelling and machine learning, with particular value placed on optimisation, ensemble methods, and portfolio construction (e.g. convex optimisation, mean‑variance and its extensions, gradient boosting, neural networks).
- Demonstrable experience in signal combination, alpha mixing, or systematic portfolio construction, ideally in a mid‑frequency setting.
- Proficiency in Python; C++ and experience in high‑performance computing environments are a plus.
- A track record of taking research into production and generating live PnL is highly valued.
- Experience with financial time‑series analysis, market microstructure, or transaction cost modelling preferred.
Quantitative Researcher (Monetisation) in London employer: Thurn Partners
As a leading quantitative proprietary HFT firm based in London, we pride ourselves on fostering a dynamic and innovative work culture that encourages collaboration and continuous learning. Our employees benefit from a strong focus on professional development, with opportunities to engage in cutting-edge research and apply their skills in a fast-paced environment. Join us to be part of a specialist team dedicated to optimising trading strategies and making a tangible impact in the financial markets.
