Job Description
Balyasny Asset Management L.P. (BAM) founded in 2001, is a global institutional investment firm. We strive to deliver consistent, uncorrelated, absolute returns in all market environments by fostering a culture of research, innovation, and collaboration. BAM exists at the intersection of finance and technology, combining the deep industry knowledge of leading portfolio managers and financial analysts with software engineers and quantitative researchers. We leverage the collective expertise of our teams to seek out new investment opportunities, analyze market conditions, minimize risk, and provide superior service to our investment partners.
With 2,000+ employees in 17 offices around the world, we embrace a culture that welcomes the free flow of ideas, promotes career development, and supports the health and well-being of our people through world-class benefits. At BAM, we are our talent. We are a growing firm that offers a multitude of professional opportunities. Through BAM's selective hiring process, we target the best and brightest in the business and strive to create an environment which attracts and retains top talent. Maintaining a culture where people are energized to come to work is paramount to our success. Our team is motivated to perform each and every day.
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Data Science & AI (DSAI) organization is a key part of BAM's continued growth. Year over year, the knowledge needed to leverage data plays an increasingly important role in the firm's core business. The analytical expertise that the Data Science & AI organization provides the firm are part of BAM's competitive advantage. The DSAI organization supports Investment Teams across all asset classes by providing research and tools powered by data science and AI to help deliver results and PnL.
As a Data Science & AI Intern , you will go through a hands-on 12-week program and solve complex, real-world problems. You will experience firsthand how data science and AI are used to enhance and support the investment process. Our internship program includes a two-week training block where you will learn how investing works at a hedge fund and get hands-on experience with our DSAI tools and environments before hitting the desk. It also offers mentorship and collaboration with senior members of the team in addition to the opportunity to expand your network with the greater intern cohort.
Single Application, Dual Consideration: By applying to the Data Science & AI Internship, you will automatically be considered for both the Data Science and Applied AI Research tracks within the DSAI organization. Our interview process is designed to assess your skills and interests across both areas, ensuring you are matched to the team and projects where you can have the greatest impact. You do not need to submit separate applications for each track.
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Data Science: Data Science Interns work on the Geospatial + Alternative Data team. In this role, you will be responsible for extracting actionable insights from our many rich alternative datasets. You will be involved at every stage of this process, including hypothesis generation, data wrangling, building and testing appropriate statistical and machine learning models, and communicating your findings to senior managers.
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Applied AI: Applied AI Research interns will be responsible for researching and implementing generative AI solutions to empower our investment teams to work more efficiently and effectively. You'll be involved in every phase of the analytics process, from research and idea generation to the hands-on development of systems to store, retrieve and derive insights from textual data. As part of the Applied AI team, you'll get to see first-hand how AI can be used to enhance and support the investment process.
Qualifications: •Master's or PhD student graduating between December 2026 and May 2027 who is pursuing a degree Computer Science, Mathematics, Statistics, Data Science with a focus on Machine Learning and/or Generative AI techniques, or another related quantitative field.
•Exceptional analytical, data processing and programming skills (at a minimum, python, numpy, pandas, scikit-learn, matplotlib and SQL)
•Exceptional understanding of statistical and machine learning concepts
•Familiarity with ETL tools and managing code repositories (GitHub)
•Experience training and fine-tuning large language and embedding models, and using these to build applications (e.g. using LangChain)
•Ability to clearly communicate complex and technical subject matters
•Results driven mindset, ability to work in an ambiguous environment, and work collaboratively within a team environment
•Experience with the following technologies is a plus: Vector Databases, OpenSearch, Apache Airflow, AWS, Spark, Databricks, Deep learning frameworks (e.g., Tensorflow, Keras and PyTorch)
•Academic or industry experience in the following fields is a plus for our Geospatial + Alt Data teams: natural science, spectral imaging, hydrology, meteorology, weather/flood modelling, computer vision, econometrics
Opportunities are available in our New York and Austin Offices.
Job Tags
Summer internship,