Balyasny Asset Management L.P.

About the Company

Balyasny Asset Management (BAM) is a diversified global investment firm founded in 2001 by Dmitry Balyasny, Scott Schroeder, and Taylor O'Malley. With over $26 billion in assets under management, BAM employs more than 2,000 people across 23 offices in the U.S. and Canada, Europe, the Middle East, and Asia. The firm's investment teams span five strategies, including Equities Long/Short, Fixed Income & Macro, Commodities, Multi-Asset Arbitrage, and Systematic. Balyasny's mission is to deliver to its investors absolute, uncorrelated returns in all market environments.

Listed Jobs

Company Name

Balyasny Asset Management L.P.

Job Title

Quantitative Research Intern

Job Description

Job title: Quantitative Research Intern Role Summary: 10‑week internship focused on elevating research abilities through hands‑on projects across multiple asset classes. Interns develop predictive models, enhance trading alphas, support quant trading infrastructure, and improve risk‑management frameworks, working closely with senior researchers and portfolio managers. Expactations: Master’s or PhD candidate graduating Dec 2026 or May 2027 in Mathematics, Statistics, Computer Science, or related quantitative field; high‑achieving bachelor’s candidates with interdisciplinary backgrounds also considered. Key Responsibilities: - Build, support, and deploy quant trading infrastructure for multi‑asset arbitrage and portfolio construction. - Develop alpha strategies using LLMs and machine‑learning techniques for long/short equity trades. - Collaborate with risk managers to refine risk‑modeling frameworks and analyze portfolio exposures. - Work with large, complex datasets to design and validate predictive models. - Conduct independent data‑driven research and present insights to senior team members. - Communicate technical findings clearly to both technical and non‑technical audiences. - Grow professional network within the intern cohort and broader research teams. Required Skills: - Strong probability and statistical theory (including ML/NLP fundamentals). - Familiarity with language models (BERT, GPT, XLNet) and related NLP research. - Proficient in Python; experience with data‑science libraries (e.g., pandas, scikit‑learn, PyTorch/TensorFlow). - Ability to handle large, heterogeneous datasets and construct predictive models. - Excellent analytical abilities and meticulous attention to detail. - Clear, concise communication of complex technical concepts. - Pragmatic, self‑motivated “can‑do” attitude in ambiguous, real‑world investment contexts. - Results‑driven, collaborative mindset. Required Education & Certifications: - Master’s or PhD in Mathematics, Statistics, Computer Science, or a closely related quantitative discipline; expected graduation Dec 2026 – May 2027. - Exceptional bachelor’s students with interdisciplinary quantitative experience may qualify. - No mandatory certifications required, but familiarity with industry tools and frameworks is beneficial.

London, United kingdom

On site

Fresher

17-12-2025