Engineer, Commodities Quantitative Development

Location:

London Department:
Technology Experience Level: Experience Professionals Contact:
Paul Krug Job  the Role Balyasny Asset Management is seeking an experienced Quantitative Engineer to support commodities trading by building, extending, and supporting custom models, reusable libraries, and analytics for Commodity Portfolio Managers and traders.

The individual will partner closely with multiple trading desks across energy and commodities, working at the intersection of quantitative modelling and software engineering. The role demands someone equally comfortable building production-grade software and translating complex business requirements from traders and researchers into scalable, maintainable technical solutions.

Responsibilities
• Build, enhance, and maintain custom tools, models, analytics, and reusable software libraries used directly by trading teams.
• Support and extend quantitative modelling frameworks, including power/energy dispatch models and related pipelines.
• Develop and maintain data pipelines, interfaces, and integrations with internal and external trading, market-data, and analytics systems.
• Partner directly with Portfolio Managers, traders, and researchers across multiple desks to understand requirements and deliver practical solutions.
• Perform day-to-day operational support and monitoring for proprietary trading systems; investigate and resolve issues promptly.
• Collaborate with cross-functional technology and platform teams to deliver reliable, scalable infrastructure.
• Identify manual or inefficient workflows and drive automation and process improvement.
• Develop and maintain clear technical documentation, including system architecture, processes, and runbooks.
• Work independently with sound engineering judgement, strong ownership, and minimal supervision.

Qualifications & Requirements
• 4+ years of hands-on software development experience, ideally supporting Portfolio Managers, traders, or investment teams.
• Strong Python development skills, including experience with scientific and data libraries such as pandas, Num Py, Sci Py, and related tooling.
• Experience designing and maintaining production-grade software, including reusable libraries, APIs, data-processing workflows, and automated testing.
• Experience building data-intensive applications or working with large-scale computational graphs, analytics platforms, or trading systems.
• Experience with Snowflake, SQL, data pipelines, or analytics workflows.
• Familiarity with AI tooling, including integrating LLMs, agentic workflows, retrieval systems, or other machine-learning-enabled applications into business processes.
• An interest in or understanding of financial modelling or derivatives pricing.
• Strong command of modern software-development practices: version control, code review, testing, CI/CD, and production monitoring.
• Strong analytical and troubleshooting skills — able to assess complex problems logically and develop pragmatic solutions.
• Excellent communication and documentation skills; able to explain technical concepts clearly to both technical and non-technical stakeholders.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.

Nice to Have
• Experience in power or energy markets (dispatch modelling, balancing mechanisms, merit order, capacity markets, or similar).
• Familiarity with mathematical optimization techniques (linear programming, mixed-integer programming, or similar frameworks).
• Proficiency in Golang, Rust or C++
• Experience with financial modelling, quantitative analytics, or derivatives pricing.
• Basic knowledge of statistics or machine learning.
• Experience acquiring, cleaning, and working with time-series, market, fundamental, or alternative datasets.