At a Glance
- Tasks: Research and develop cutting-edge trading strategies using AI and quantitative methods.
- Company: Leading AI-driven hedge fund with a focus on innovation.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on continuous learning and development.
- Why this job: Join a team of world-class experts and make an impact in global markets.
- Qualifications: Experience in quantitative research and proficiency in Python required.
The predicted salary is between 60000 - 80000 £ per year.
We are partnering with a leading AI-driven systematic multi-strategy hedge fund that is looking to hire an exceptional Quantitative Researcher to develop and enhance systematic trading strategies across Equities, FX, Rates, Macro, and Commodities. In this role, you will research, design, and deploy alpha signals and systematic investment models across global markets. Working alongside world-class researchers, machine learning specialists, and engineers, you will leverage cutting-edge AI techniques, alternative datasets, and rigorous quantitative research to identify persistent market inefficiencies and build scalable, production-grade trading strategies.
What we're looking for:
- Strong experience researching and developing systematic statistical arbitrage or quantitative trading strategies across one or more asset classes, including Equities, FX, Rates, Macro, or Commodities
- Proven track record of generating alpha through quantitative research, signal development, and portfolio construction
- Advanced quantitative, statistical, and machine learning expertise with experience developing predictive models for financial markets
- Highly proficient in Python for quantitative research, data analysis, backtesting, and production-level implementation
- Experience working with large-scale financial, alternative, and unstructured datasets to generate differentiated investment insights
- Strong understanding of market microstructure, execution, transaction costs, and risk management across systematic trading strategies
- Experience building robust research pipelines and evaluating strategies through rigorous testing, validation, and performance attribution
- Familiarity with modern AI and machine learning techniques, including supervised and unsupervised learning, feature engineering, and model optimization
- Ability to collaborate closely with researchers, engineers, and portfolio managers to translate research into live production strategies
- A curious, research-driven mindset with strong ownership across the entire research lifecycle, from idea generation through live deployment
If this role aligns with your background, apply directly or recommend a colleague who would be a strong fit.
