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🚀 Internship

Data Scientist (PhD), Commodities Investment Teams (Fall Internship)

🚀 Off-cycle Internship


AI generated summary

  • The candidate must have a PhD in a STEM field, research experience in simulation or deep learning, strong coding skills in Python/SQL, knowledge of statistical modeling methods, and excellent communication and organizational skills.
  • As a Data Scientist intern at Balyasny Asset Management, you will collaborate with the investment team to explore innovative data applications, conduct quantitative research projects, analyze forecast/model accuracy, and test new datasets for improving existing models.

Off-cycle Internship




Rolling basis


  • Balyasny Asset Management is looking for an exceptional Data Science Fall Associate, to intern for 6-12 months, to work on a Commodities Portfolio Management team on projects related to data gathering, data analysis, and data-driven idea generation. This is an excellent opportunity to work on cutting-edge research at a leading hedge fund, offering hands-on experience at the intersection of commodities trading and data science.
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  • Availability to intern for 6 – 12 Months
  • PhD degree in Computer Science, Mathematics, Engineering, Data Science, or any STEM related field. Pure Science majors with strong coding skills are also welcome to apply
  • Research focused on simulation, reinforcement learning or adversarial deep learning
  • Prior publications and evidence of application/previous work experience preferred
  • Strong analytical and data processing skills (Python/SQL), and knowledge of version control (Git)
  • Knowledge of common statistical modelling methods and algorithms
  • Self-starter, results-driven attitude with a great desire to learn and ability to multitask
  • Strong written and verbal communication skills, outstanding attention to detail and strong organisation skills
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Education requirements


Area of Responsibilities



  • Collaborate directly with Portfolio Manager and team to brainstorm creative uses for data in the investment process
  • Conduct independent project-oriented quantitative research using a variety of datasets
  • Conduct forecast or model error analysis, and provide findings to improve forecast/model accuracy
  • Identify, ingest, and analyze new datasets to test improvement/enhancement capabilities for existing models and infrastructure
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Work type

Full time

Work mode




Rolling basis