🚀 Internship
Data Scientist (PhD), Commodities Investment Teams (Fall Internship)
Balyasny Asset Management L.P.
•
16d ago
🚀 Off-cycle Internship
London
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.
Description
- 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.
Requirements
- 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
Education requirements
STEM
PhD
Area of Responsibilities
Data
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
Details
Work type
Full time
Work mode
office
Location
London