Our client is a leading global multi-strategy investment manager with a significant presence across commodities markets. The team combines fundamental expertise, quantitative research, technology, and alternative data to uncover investment opportunities across energy, metals, agriculture, and broader commodity markets. Technology and research are viewed as key competitive advantages, with engineers and researchers working directly alongside portfolio managers to develop forecasting models, research platforms, and data-driven investment processes.

Direct commodities experience is not required. The team is primarily focused on identifying exceptional engineers with strong backgrounds in software engineering, quantitative problem solving, machine learning, forecasting, data-intensive systems, or research infrastructure, regardless of industry experience.

We are seeking a Research Engineer to help build the next generation of research and forecasting capabilities for a systematic commodities investing team. This individual will partner closely with portfolio managers, quantitative researchers, and data scientists to develop scalable research infrastructure, onboard new datasets, improve forecasting workflows, and accelerate the research lifecycle from idea generation to production deployment.

The role sits at the intersection of software engineering, quantitative research, data science, and commodities investing. Successful candidates will enjoy solving complex problems involving large datasets, machine learning, simulation, optimization, forecasting, and research tooling while having direct visibility into how their work impacts investment decisions.

This is an opportunity to join a highly collaborative team where engineers have meaningful ownership, close interaction with investment professionals, and the ability to influence both technology and research direction.