This listing doesn't post a salary. Most similar roles pay
$114,225–$234,550.
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.
The Quantitative Researcher - Multi-Asset Arbitrage (Summer Internship) joins the research team to develop quantitative practices including risk management, big data analysis, AI, and LLM applications. This intern will participate in a ten-week program focused on solving complex problems to enhance investment and trading frameworks while building, supporting, and integrating globally accessible quant trading infrastructure. The role involves collaborating with Portfolio Managers and Quant Researchers to build necessary toolkits for the Multi-Asset Arbitrage team. Candidates must possess programming proficiency in Python and strong knowledge of probability, statistics, machine learning, and natural language processing. Experience includes working with large, complex datasets, building predictive models, and familiarity with models like BERT, GPT, and XLNet. The position focuses on solving real-world investment problems through data-driven research and technical communication within a collaborative team environment.
Build, support, and integrate globally accessible quantitative trading infrastructure.
Develop models for risk management, big data analysis, AI, and LLM applications.
Enhance investment and trading frameworks and strategies to solve real-world problems.
Create requisite toolkits in collaboration with Portfolio Managers and Quant Researchers.
Analyze large, complex datasets to build predictive models.
Apply machine learning and natural language processing techniques to quantitative research.
Communicate complex technical subject matters clearly to stakeholders.
What we're looking for
Pursuing a Bachelor's degree in Mathematics, Statistics, Computer Science, or a related quantitative field with graduation between Winter 2027 and Summer 2028.
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.
Familiarity with language models such as BERT, GPT, and XLNet, and NLP related publications (preferred).
Outstanding analytics skills and attention to detail.
Ability to clearly communicate complex and technical subject matters.
Python
C++
Java
SQL
R
MATLAB
Machine Learning
Data Science
Time-series Analysis
Optimization
Statistical Learning
Tableau
Power BI
Portfolio Construction
Quantitative Research
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