Quantitative Researcher - Options (HFT/Intraday)
Quantitative Researcher - Options Alpha Research
Location: London
About the Role
Our client is seeking a highly quantitative and research-driven individual to join their Options Alpha Research team. This role sits at the intersection of quantitative research, systematic trading, and data science, with a primary focus on developing predictive signals and alpha models across listed options markets.
You will work alongside experienced researchers, traders, and technologists to identify market inefficiencies, build scalable research pipelines, and translate quantitative insights into production-ready trading strategies. The successful candidate will have end-to-end ownership of the research process, from idea generation and data analysis through to implementation, monitoring, and ongoing optimisation.
Key Responsibilities
- Research and develop predictive alpha signals for systematic options trading strategies.
- Analyse large and diverse datasets to identify statistical patterns, market inefficiencies, and trading opportunities.
- Design, test, and validate quantitative models across options markets, with a focus on signal robustness and scalability.
- Conduct exploratory research into new datasets, alternative data sources, and innovative modelling techniques.
- Collaborate closely with traders, quantitative developers, and technology teams to deploy research into production.
- Implement signals, datasets, and models within the firm's global trading infrastructure.
- Monitor model performance, signal decay, and portfolio behaviour, recommending enhancements where appropriate.
- Share research findings, methodologies, and best practices across the broader research organization.
- Lead the full strategy research lifecycle, from hypothesis generation and backtesting through to implementation and performance evaluation.
Required Qualifications
- Advanced degree (Master's or PhD preferred) in Mathematics, Statistics, Physics, Computer Science, Engineering, Data Science, or a related quantitative discipline.
- Strong understanding of statistical modelling, probability, machine learning, and quantitative research methodologies.
- Excellent programming skills in Python; experience with C++, Java, or other performance-oriented languages is advantageous.
- Proven ability to work with large-scale financial datasets and conduct rigorous empirical research.
- Strong problem-solving skills and a highly analytical mindset.
- Ability to communicate complex quantitative concepts clearly to traders, researchers, and engineers.
- Demonstrated ability to operate independently while thriving in a collaborative team environment.
Preferred Experience
- Previous experience researching systematic trading strategies within options, volatility, derivatives, or broader quantitative trading environments.
- Understanding of option pricing, volatility modelling, market microstructure, and derivatives trading.
- Experience applying machine learning, AI, NLP, or advanced statistical techniques to financial markets.
- Familiarity with backtesting frameworks, production research environments, and live signal monitoring.
- Track record of generating profitable quantitative signals or improving systematic trading performance.
What they're Looking For
- Intellectual curiosity and a passion for financial markets.
- A scientific approach to problem solving and hypothesis testing.
- Strong ownership mentality with the ability to drive research projects independently.
- Attention to detail and the ability to manage multiple research initiatives simultaneously.
- A collaborative mindset and willingness to share ideas, research, and knowledge with colleagues.
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