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 in all market environments. BAM has offices in Chicago, New York, Greenwich, San Francisco, Hong Kong and London.

At BAM, we are our talent. We are a growing firm that offers a multitude of professional opportunities. Through BAM’s selective hiring process, we target the best and brightest in the business, and strive to create an environment which attracts and retains top talent. Maintaining a culture where people are energized to come to work is paramount to our success. Our team is motivated to perform each and every day.

As a result, BAM has built a reputation as a firm that provides the tools necessary for talented individuals to achieve their goals and reach their highest potential.

ROLE OVERVIEW:

BAM is seeking an experienced Quantitative Analyst focused on developing, implementing, and optimizing data-driven trading strategies across credit and municipal bond markets. The candidate will interact will collaborate with the portfolio manager, traders and technologists to analyze data, build statistical models, and generate actionable investment insights. This person will need to be a strong communicator, able to multi-task and have the ability to excel in a fast-paced trading environment.

KEY RESPONSIBILITIES

• Support portfolio manager and analysts in building out bespoke alpha research tools using in-house analytics

• Analyze large datasets related to credit and municipal bonds to identify inefficiencies, opportunities, and risks in the for credit and muni markets.

• Work closely with the investment team and build valuation tools and screeners to improve their trading and filtration process

• Test various trading strategies, perform adhoc research and deliver the results via Excel/Python framework

• Support trading and risk management with scenario analysis, relative value, and basis trading analytics.

• Perform with minimum supervision and exercise sound judgment

REQUIRED QUALIFICATIONS

• Advanced degree (MS/PhD preferred) in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, or Finance.

• 2+ years of experience in a quantitative or research role (preferably in fixed income/credit/munis).

• Strong programming skills in Python.

• Deep understanding of credit products and municipal bonds; familiarity with market data sources (TRACE, EMMA, Bloomberg, etc.).

• Experience with statistical/ML modeling and backtesting frameworks.

• Self-motivated, detail-oriented, and able to communicate complex ideas clearly to technical and non-technical audiences.

THE IDEAL CANDIDATE WILL BE SOMEONE WHO DEMONSTRATES 

• Experience working with traders or in a trading environment.

• Familiarity with risk management, portfolio construction, or pricing in fixed income.

• Strong desire to work collaboratively with the team

• Documentation skills – ability to represent ideas, requirements, and problems in clear and concise documents

• Outstanding attention to detail and strong organization skills