Quantitative Developer - Systematic Strategies (Summer Internship)

Balyasny Asset Management is seeking exceptional Quantitative Developer Interns to join our Systematic Business.

Our investment process relies on robust, efficiently designed software to support research, investment decision-making, and trading.

You will have the opportunity to contribute to meaningful projects at the intersection of quantitative finance and technology. Potential workstreams may include systems design, data-processing, optimization, machine learning, analytics, and research infrastructure.

This is an opportunity to gain hands-on experience solving cutting-edge quantitative engineering challenges at a leading multi-strategy investment firm.

RESPONSIBILITIES

• Design and build scalable software components that support systematic investment workflows.
• Develop and improve data-processing, analytics, optimization, and machine-learning tools used by the Systematic Business.
• Work with Kubernetes-based deployments and contribute to more efficient, reliable development and production processes.
• Enhance real-time monitoring, alerting, and metrics to improve visibility into data pipelines and system health.
• Collaborate with quantitative researchers, quantitative developers, and business stakeholders to translate investment and operational requirements into practical technical solutions.
• Communicate progress, technical decisions, and results clearly to team members and stakeholders.

 QUALIFICATIONS & REQUIREMENTS

• Bachelor’s and Master's student graduating between Winter 2027 and Spring/Summer 2028 who are pursuing a degree in Computer Science, Software Engineering, Computer Engineering, or a related STEM discipline, with strong programming experience.
• Strong proficiency in Python and/or C++; experience writing clean, efficient, and maintainable code is preferred.
• Interest in quantitative finance, systematic investing, market-data systems, or research and trading infrastructure.
• Familiarity with data engineering, distributed systems, cloud computing, Kubernetes, optimization, or machine learning is a plus.
• Self-starter with a results-oriented mindset, strong intellectual curiosity, and a desire to learn quickly.
• Excellent attention to detail, problem-solving ability, and communication skills.