Quantitative Researcher – Multi-Asset Arbitrage

Balyasny Asset Management; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

BAM is seeking an experienced Quantitative Researcher to build, support, and integrate globally accessible quant trading infrastructure. You will collaborate with portfolio managers and researchers to develop toolkits and evaluate strategies in a fast-paced trading environment.

The role requires a Master or PhD in a technical field, with strong Python skills and optional C++ experience. You will contribute to back testing, simulation, and market data workflows while documenting methodologies.

Qualifications

• Master degree or PhD in a technical field (Math, Physics, Engineering, Computational Finance).
• Proven experience as a researcher or developer in the quant group within an investment bank or hedge fund.
• Proficient in Python; C++ experience desirable.
• Strong analytical abilities, attention to detail, and clear documentation.

Responsibilities

• Leverage analytics libraries and trading infrastructure for research.
• Build valuation tools and screeners to improve trading processes.
• Test trading strategies and deliver results via Python/Excel framework.
• Document models, strategies, and tools developed.
• Collaborate with business users and platform developers to gather requirements.

Skills

Analytical thinking

Communication

Documentation

Collaboration

Education

Master's degree or PhD in Math/Physics/Engineering/Computational Finance

Tools

Python

C++

Job description

Location: New York, LondonDepartment: TechnologyExperience Level: Experience ProfessionalsContact: Paul KrugJob ID: REQ8089

ROLE OVERVIEW:

BAM is seeking an experienced Quantitative Researcher with expertise in building, supporting and integrating globally accessible quant trading infrastructure. The candidate will interact with portfolio managers and quant researchers to building requisite toolkits. The optimal candidate will have prior experience at a financial services organization with an exceptional technical background and in-depth knowledge of quantitative trading systems including back testing, simulation, performance testing and market data. 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 include:

• Leverage the Credit and Convertible Bonds analytics library and trading infrastructure made up of vendor and internally developed platforms for research purposes
• 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
• Assist in the buildout of the internal Credit, Convertible Bond and securitized products (CMBS, CLO, ABS) analytics
• Assist in the buildout of Systematic Credit and securitized products strategies
• Work closely with business users and platform developers to capture requirements and handle onboarding and integration of vendor models and datasets.
• Develop written documentation of the models, strategies and tools developed
• Perform with minimum supervision and exercise sound judgment
• Help identify and automate manual processes

Qualifications & Requirements:

• Master degree/PhD in a technical area, such as Math, Physics, Engineering or Computational Finance.
• Proven work experience as a researcher or developer in the quant group within an investment bank or hedge fund.
• Proficient in programming – Python required, C++ is desirable.
• Experience building trading tools is desirable.
• Experience in alpha research and signal generation is desirable.
• Basic understandings derivatives modeling. Knowledge of Credit products or Convertible Bonds is desirable
• High degree of accuracy and attention to detail
• Analytical skills – Ability to troubleshoot and logically assess problems and determine solutions
• Documentation skills – ability to represent ideas, requirements, and problems in clear and concise documents
• Desire to work in a collaborative environment, enhancing a shared toolset