Quantitative Researcher – Multi-Asset Arbitrage

Balyasny Asset Management L.P. (BAM), founded in 2001, is an institutional investment firm dedicated to delivering consistent, uncorrelated absolute returns across market environments. BAM has offices in Chicago, New York, Greenwich, San Francisco, Hong Kong, and London.

At BAM, our people are our edge. We are a growing firm that offers a wide range of professional opportunities and seeks to attract and retain exceptional talent. Through a highly selective hiring process, we look for individuals with strong technical skill, intellectual curiosity, and a drive to solve complex investment problems. We aim to foster an environment where talented professionals are empowered with the tools, autonomy, and collaboration needed to perform at the highest level.

As a result, BAM has built a reputation as a firm that equips high-performing individuals to achieve their goals and maximize their potential.

Role Overview

BAM is seeking an experienced Quantitative Researcher / CLO Quant to support investment teams focused on structured credit and leveraged finance, with an emphasis on CLOs, loan portfolios, and related relative value opportunities. This individual will work closely with portfolio managers, analysts, traders, and technologists to develop and enhance the research, analytics, and portfolio tools required to evaluate, monitor, and trade CLO investments.

The ideal candidate will have experience building scalable analytics and research infrastructure in a buy-side or sell-side credit environment, with strong knowledge of CLO structures, bank loans, credit cash flows, portfolio construction, and scenario analysis. The role requires excellent technical skills, strong communication, and the ability to operate effectively in a fast-paced investment setting.

Key Responsibilities

• Develop and enhance valuation, surveillance, and screening tools for CLOs, loan portfolios, and related credit instruments

• Support investment decision-making through scenario analysis, relative value analysis, and risk monitoring across CLO portfolios and underlying loan exposures

• Research and back-test CLO investment strategies, delivering outputs through Python- and Excel-based frameworks

• Collaborate with PMs, analysts, and other quants to translate research into production-ready code

• Document model assumptions, methodology, code architecture, and user-facing APIs clearly and thoroughly

Required Qualifications

• Bachelor’s or Master’s degree in Financial Engineering, Mathematics, Statistics, Physics, Computer Science, or a related field

• 3+ years of professional experience in a quantitative role, with strong hands-on Python skills

• Experience with numerical libraries and data tools such as NumPy, SciPy, Pandas, Matplotlib, and Plotly

• Experience building investment tools for credit markets; CLO or other securitized products experience strongly preferred

• Experience with Intex for cash-flow, scenario, and deal-structure analytics

• Strong software engineering skills, including Git, CI/CD pipelines, and code review practices

Preferred Skills

• Strong coding experience in Python; prior exposure to C++ in quant libraries is a plus

• Experience building RESTful APIs or microservices using FastAPI or Flask

• Understanding of SQL/NoSQL databases and data warehouse solutions

• Background in machine learning techniques applied to rates or credit modeling

• Experience with cloud platforms such as AWS, GCP, or Azure

The Ideal Candidate Will Demonstrate

• A strong desire to work collaboratively with portfolio managers, analysts, traders, and developers

• Excellent problem-solving ability and judgment in identifying practical, high-impact solutions

• The ability to prioritize and manage multiple projects simultaneously in a fast-paced environment

• Strong documentation skills, with the ability to communicate ideas, assumptions, requirements, and issues clearly and concisely

• Outstanding attention to detail and strong organizational discipline