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For Companies At a Glance
- Tasks: Join a dynamic team to analyze data and generate investment ideas in commodities.
- Company: Balyasny Asset Management is a leading hedge fund known for innovative research.
- Benefits: Gain hands-on experience with potential for full-time employment after the internship.
- Why this job: Work at the cutting edge of data science and commodities trading in a collaborative environment.
- Qualifications: PhD in relevant fields, strong analytical skills, and proficiency in Python/SQL required.
- Other info: Ideal for self-starters eager to learn and make an impact in finance.
OVERVIEW
Balyasny Asset Management is looking for an exceptional PhD Data Scientist intern to join BAM for 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. If the internship is successful, there is an opportunity to convert into a full-time employee.
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.
QUALIFICATIONS & REQUIREMENTS
- Availability to intern for 12 months on a full-time basis.
- PhD degree in Reinforcement Learning, Simulations, Synthetic Data or Machine Learning.
- 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.
- Background in atmospheric sciences and experience with weather modeling and prediction.
- 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 organization skills.
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PhD Data Scientist - Commodities Investment Team (12 month Internship) employer: Balyasny Asset Management LP
Contact Detail:
Balyasny Asset Management LP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PhD Data Scientist - Commodities Investment Team (12 month Internship)
✨Tip Number 1
Make sure to familiarize yourself with the latest trends in commodities trading and data science. This will not only help you during the interview but also show your genuine interest in the field.
✨Tip Number 2
Network with professionals in the commodities investment space. Attend relevant conferences or webinars, and connect with people on LinkedIn who work at Balyasny Asset Management or similar firms.
✨Tip Number 3
Prepare to discuss your previous research projects in detail, especially those related to reinforcement learning or simulations. Be ready to explain how your findings can be applied to real-world scenarios in commodities trading.
✨Tip Number 4
Showcase your programming skills by working on a small project that involves data analysis or model building. This hands-on experience can be a great talking point during your interview and demonstrate your capabilities.
We think you need these skills to ace PhD Data Scientist - Commodities Investment Team (12 month Internship)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD research and any relevant experience in data science, particularly in reinforcement learning or simulations. Emphasize your analytical skills and any prior publications.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the internship and how your background aligns with the responsibilities of the role. Mention specific projects or experiences that demonstrate your ability to contribute to the Commodities Portfolio Management team.
Showcase Technical Skills: Clearly outline your proficiency in Python, SQL, and Git in your application. Provide examples of how you've used these tools in previous projects or research to solve complex problems.
Highlight Communication Skills: Since strong communication skills are essential, include examples of how you've effectively communicated complex data findings in your past work or research. This could be through presentations, publications, or collaborative projects.
How to prepare for a job interview at Balyasny Asset Management LP
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to reinforcement learning or simulations. Highlight any publications you have and how they relate to the role.
✨Demonstrate Your Technical Skills
Make sure to showcase your proficiency in Python and SQL during the interview. You might be asked to solve a problem or analyze a dataset, so practice coding challenges beforehand.
✨Prepare for Quantitative Questions
Expect questions that test your understanding of statistical modeling methods and algorithms. Brush up on common techniques and be ready to explain how you've applied them in your work.
✨Communicate Clearly and Effectively
Since strong communication skills are essential, practice explaining complex concepts in simple terms. Be concise and clear in your responses, and don't hesitate to ask for clarification if needed.
