Quantitative Researcher, Systematic, Multi-Asset Arbitrage (Intern)

Balyasny Asset Management

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NY
Employment
Intern
Posted
28 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

How this pay compares to similar roles

Similar $177k
$103k most similar roles pay here $252k

This listing doesn't post a salary. Most similar roles pay $117,471–$237,321.

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 59 open roles on FindRole.

Listed pay typically runs $175,000–$250,000 across 30 roles with salary data.

Most-posted roles

View all roles at Balyasny Asset Management

At a glance

TL;DR · Quantitative Researcher, Systematic, Multi-Asset Arbitrage (Intern)

As a Quantitative Researcher - Systematic, Multi-Asset Arbitrage (Summer Internship), you will join the research team to solve complex problems by enhancing investment and trading frameworks. You will work on various initiatives including analyzing textual data with advanced NLP models to develop trading signals, building globally accessible quant trading infrastructure, developing alphas using LLM and machine learning methods for equity teams, and conducting factor model research for portfolio construction. The role requires proficiency in Python along with strong knowledge of probability, statistics, and machine learning. You will work with large, complex datasets to build predictive models while utilizing tools like BERT, GPT, and XLNet. This position focuses on the technical challenges of risk management, big data analysis, and developing automated trading strategies across multiple asset classes within a professional investment environment.

What you'll do

  • Analyze textual data using advanced NLP models to develop actionable trading signals.
  • Build, support, and integrate globally accessible quantitative trading infrastructure.
  • Develop alpha signals utilizing LLM and machine learning methods to enhance trading strategies.
  • Improve risk management framework models and conduct research analysis on portfolio construction.
  • Conduct factor model research and build tools for equity factors used across the firm.
  • Process large, complex datasets to build predictive models for investment processes.
  • Solve complex real-world problems to improve investment and trading frameworks.

What we're looking for

  • Must be a Bachelor's or Master's student graduating between Winter 2027 and Spring/Summer 2028.
  • Pursuing a degree in Mathematics, Statistics, Computer Science, or a related quantitative field.
  • Proficiency in Python programming.
  • Strong knowledge of probability and statistics, including machine learning and natural language processing.
  • Experience working with large, complex datasets and building predictive models.
  • Prior independent research experience in a data-driven environment.
  • Outstanding analytics skills and attention to detail.
  • Ability to clearly communicate complex and technical subject matters.
  • Familiarity with language models such as BERT, GPT, and XLNet, and NLP related publications (preferred).

More like this

Similar roles

Quantitative Researcher/Trader, Associate

Balyasny Asset Management

Hong Kong, China +3 78 days ago $150,000$225,000
Python pandas Statistical Arbitrage Back-testing Data Analysis Quantitative Research Portfolio Management Trade Logs
1+ yrs exp

Quantitative Research Markets Summer Internship Associate

JPMorgan Chase

New York, NY 38 days ago
Python C++ Machine Learning Data Science Quantitative Modeling Statistical Modeling Algorithmic Trading Financial Engineering Portfolio Optimization Risk Management Options Pricing Theory Alpha Research Data Analytics