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Work on high-performance systematic trading models for precious metals markets in London.
Leverage Python and KDB/q skills to build scalable, low-latency trading systems.
Title
Title: E-Trading Quant
Location
Location: London, United Kingdom
Description
Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Overview
Job Description: You will be responsible for the development, implementation, and optimisation of systematic trading and pricing models across precious metals markets. The role requires a strong understanding of the dynamics between futures and spot markets, with a particular focus on basis risk, arbitrage relationships, and Exchange for Physicals (EFPs). Working closely with trading and technology teams, you will play a key role in bringing models from research into production, ensuring robustness, scalability, and performance in live trading environments.
Responsibilities
- Develop and enhance quantitative models for pricing and systematic trading across precious metals products
- Analyse the relationship between futures and spot markets, including basis dynamics, liquidity considerations, and EFP mechanisms
- Design and implement strategies that capture inefficiencies and optimise execution across electronic markets
- Work with large datasets to perform rigorous statistical analysis, signal generation, and backtesting
- Partner closely with traders to translate market insights into quantitative strategies
- Collaborate with technology teams to deploy models into production systems, ensuring low-latency and high-performance execution
- Continuously monitor, evaluate, and improve model performance in live trading environments
- Contribute to the ongoing development of the team’s quantitative research framework and infrastructure
Skills
- Strong academic background in a quantitative discipline (e.g. Mathematics, Physics, Engineering, Computer Science, or similar)
- Proven experience developing quantitative models within trading, pricing, or market-making environments
- Deep understanding of futures vs. spot market dynamics, including basis risk and arbitrage relationships
- Experience working with large, complex datasets and applying advanced statistical and modelling techniques
- Strong programming skills in Python (essential), including data analysis and numerical libraries
- Experience with KDB+/q and/or Java is highly desirable
- Solid understanding of systematic trading, electronic markets, and market microstructure
- Experience taking models from research through to production deployment