Quantitative Research Intern (AI)

Location: London, United Kingdom

Company

Diversified trading firm operating with proprietary capital across fixed income, ETFs, equities, FX, commodities, energy, real estate, venture capital, and cryptoassets.

What you will do

• Create practical solutions for systematic equity trading or fixed income options desks.
• Analyze market data, historical trends, and relationships across multiple asset classes.
• Develop mathematical models and apply quantitative and machine learning methods to identify trading opportunities.
• Build and refine research infrastructure and tools with traders and quantitative researchers.
• Use simulation, back-testing, and validation to evaluate proposed models.

Requirements

• Pursuing a Bachelor’s, Master’s, or PhD in Statistics, Optimisation, Machine Learning, Artificial Intelligence, Quantitative Finance, or a related technical field.
• Expected graduation between December 2027 and October 2028.
• Proficiency in Python and machine learning tools including NumPy, pandas, and scikit-learn.
• Experience exploring large datasets and strong analytical and problem-solving skills.
• Knowledge of statistics, probability theory, stochastic calculus, and numerical algorithms such as finite differences and Monte Carlo simulation.
• Strong written and verbal communication skills for reporting research results and methodologies.

Nice to have

• Exposure to Natural Language Processing or High-Performance Computing.
• Publication in a top-tier journal focused on Natural Language Processing or High-Performance Computing.

Culture & Benefits

• Meaningful summer projects advised by traders.
• Mentorship with an experienced professional, including discussions of goals, challenges, and development.
• Fully furnished housing close to the office.
• Educational, social, and team-building activities during the internship.
• Options and technology immersion courses covering the intersection of trading and technology.
• Work environment emphasizing autonomy, curiosity, integrity, innovation, and challenging consensus.