Global Markets Quantitative Strategies & Data Group (QSDG) Summer Associate Program – 2027

Location: New York, NY

Business Overview

At Bank of America, we are driven by a shared purpose to help make financial lives better through the power of every connection. Our solutions span the complete range of advisory, capital raising, banking, treasury and liquidity, sales and trading, and research capabilities. We foster an inclusive, collaborative workplace where talented individuals can grow their careers, make meaningful contributions, and create lasting impact for clients, communities, and shareholders.

Our Global Markets business offers sales and trading services, including research, to institutional clients across fixed-income, credit, currency, and commodity and equity businesses. Global Markets product coverage includes securities and derivative products in both the primary and secondary markets.

About the Team

Quantitative Strategies and Data Group (QSDG) develops quantitative models, analytics and data-driven solutions that power decision-making across Global Markets. Working at the intersection of quantitative finance, data science and AI, we partner closely with traders, sales teams and technologists to solve complex market problems and deliver measurable business impact. We collaborate across business lines and are guided by the highest standards of governance, ethics and scientific rigor.

Program Overview & Responsibilities

Our summer internship program is designed to offer you an opportunity to apply your quantitative skills in an exciting and fast-moving environment. You will gain first-hand experience of the kinds of problems the trading business faces, and the vital role analytical skills play in solving them. As a quantitative strategist you will focus on a specific product area within the overall group.

Responsibilities vary with specific assignments, but examples could include:

• Develop, enhance, and implement pricing, risk, and analytics models for derivative products and trading strategies
• Conduct quantitative analysis of financial markets, market trends, trading performance, and market structure
• Apply statistical, machine learning, and AI techniques to analyze large datasets and generate actionable insights
• Partner with traders, technologists, and other stakeholders to research, design, and implement quantitative trading signals, systematic hedging strategies, and algorithmic trading solutions
• Analyze, test, and optimize existing quantitative models, frameworks, and computational methods to improve performance and scalability
• Develop and optimize electronic trading and market-making algorithms across execution and liquidity provision workflows
• Build tools, analytics, and automation solutions that enhance trading efficiency, risk management, profitability, and operational effectiveness

• Leverage modern AI technologies and agentic workflows to accelerate research, automate processes, and support data-driven trading and investment decisions

Training and Development

Your training and development is our top priority with extensive formal training offered at the start of the program in addition to on-the-job support, educational speaker events and mentorship throughout.

What We Are Looking For

Essential Qualifications

• Candidates are required to be enrolled at an accredited college or university pursuing a PhD or Master’s in a relevant quantitative field such as mathematics, physics, engineering, artificial intelligence, operations research, computer science, financial mathematics, computational finance, or financial engineering
• Must have excellent analytical, modelling and problem-solving skills.
• Ability to work effectively in a fast-paced trading environment, both independently and as part of cross-functional teams.
• Excellent communication skills with the ability to explain complex quantitative concepts to both technical and non-technical audiences.
• Strong programming skills. Python is strongly preferred; experience with Java/C++ is also valued.

Preferred Qualifications

• Experience with numerical methods, stochastic modelling and computational finance techniques
• Knowledge of financial markets, trading workflows and derivative products across one or more asset classes
• Solid understanding of derivatives modelling, option pricing theory and risk management concepts
• Experience applying machine learning, AI or advanced statistical techniques to real-world quantitative or financial problems

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