Quick summary

Work type
On-site
Location
New York, NY
Salary
$200,000–$275,000 / yr
Posted
3 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $175k
This role $238k
$124k most similar roles pay here $291k

This role pays more than 92% of similar roles. Most pay $141,383–$208,830 — the shaded band above. At the midpoint, this role pays about $238k versus about $175k for comparable roles.

Based on 240 similar postings.

Employer

About Balyasny Asset Management

Balyasny Asset Management (BAM) is a global multi-manager hedge fund offering diversified investment strategies across equities, macro, commodities, and systematic trading.

Balyasny Asset Management currently has 47 open roles on FindRole.

Listed pay typically runs $175,000–$242,500 across 26 roles with salary data.

Most-posted roles

View all roles at Balyasny Asset Management

At a glance

TL;DR · Job Detail

Balyasny Asset Management L.P. seeks a senior Quantitative Researcher to join its multi-asset arbitrage team in New York, focusing on structured credit and leveraged finance with an emphasis on Collateralized Loan Obligations (CLOs). This role involves developing and enhancing valuation, surveillance, and screening tools for CLO investments using Python and Excel frameworks. The researcher will collaborate closely with portfolio managers, analysts, and technologists to support investment decision-making through scenario analysis and risk monitoring. Essential qualifications include a strong background in quantitative finance, hands-on experience with Python and numerical libraries like NumPy and Pandas, and familiarity with Intex for cash-flow analytics. Preferred skills encompass cloud platform expertise, RESTful API development, and machine learning techniques applied to credit modeling. The ideal candidate will excel in a fast-paced environment, demonstrating robust technical skills and the ability to document complex models effectively.

What you'll do

  • Develop and enhance valuation tools for CLOs and loan portfolios.
  • Conduct scenario analysis to support investment decision-making in CLOs.
  • Back-test CLO investment strategies using Python-based frameworks.
  • Collaborate with teams to translate research into production-ready code.
  • Document model assumptions, methodologies, and user-facing APIs thoroughly.

What we're looking for

  • Bachelor’s or Master’s degree in a quantitative field such as Financial Engineering, Mathematics, Statistics, Physics, or Computer Science.
  • At least 3 years of professional experience in a quantitative role with strong Python skills.
  • Experience building investment tools for credit markets and familiarity with CLOs or other securitized products.
  • Proficiency with numerical libraries like NumPy, SciPy, Pandas, Matplotlib, and Plotly.
  • Strong software engineering background including Git, CI/CD pipelines, and code review practices.
  • Ability to develop and enhance valuation, surveillance, and screening tools for CLOs and loan portfolios.

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