Quantitative Strategies and Data Group, 2027 Summer Associate - London

Full job description

About Us 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. The team: Quantitative Strategies and Data Group (QSDG) uses models, data, and analytics to develop and deliver impactful solutions to sales and trading teams across Global Markets, guided by the highest standards of governance, ethics and scientific rigor. Programme Overview Our summer internship programme offers the opportunity to apply your quantitative skills in an exciting and fast-moving environment, gaining first-hand experience of the problems the trading business faces and the role analytical skills play in solving them. Responsibilities: - Develop and enhance pricing, risk and analytics models for complex derivative products - Apply statistical, machine learning and AI techniques to analyse large market datasets, client interactions and trading performance - Partner with traders to research, design and implement quantitative trading signals and strategies - Build frameworks and tools to improve trading efficiency, risk management and profitability - Develop and optimise electronic trading algorithms - Leverage AI technologies and agentic workflows to automate research and accelerate model development Eligibility Candidates are required to be pursuing a Bachelor's or Master's degree from an accredited college or university with a completion time frame between September 2027 and July 2028. On track for a minimum 2:1 degree classification (or equivalent). What we are looking for Essential: - Excellent analytical, modelling and problem-solving skills - Ability to work effectively in a fast-paced trading environment, independently and in cross-functional teams - Excellent communication skills, able to explain complex quantitative concepts to technical and non-technical audiences - Strong programming skills; Python strongly preferred, Java/C++ also valued - Degree in mathematics, statistics, physics, computer science, engineering or a related quantitative discipline Desired: - Experience with numerical methods, stochastic modelling and computational finance techniques - Knowledge of financial markets, trading workflows and derivative products - Understanding of derivatives modelling, option pricing theory and risk management concepts - Experience applying machine learning, AI or advanced statistical techniques to real-world financial problems