Overview
The organization is seeking a Quantitative Researcher to join its systematic commodities trading team and build forecasting models that support its strategies.
You will join a team of 5 that researches and trades systematic strategies across commodity futures. Work closely with traders and an engineer to deliver research ideas into production-grade strategies.
Responsibilities
- Research and develop systematic strategies across futures, with a strong emphasis on commodities, applying statistical and machine learning
- Own the research process end to end, including:
- experiment design
- dataset generation
- time-series analysis
- feature engineering
- model building
- backtesting
- productionizing the signal
- Run research workloads efficiently on a distributed, cloud-based compute platform, and partner with the platform engineer to shape new capabilities
- Collaborate closely with traders, engineers, and core technology teams to identify the best expression of new ideas in the portfolio
- Document research findings with academic rigor
Qualifications
- BS, MS, or PhD in Statistics, Mathematics, Physics, Computer Science, Engineering, Quantitative Finance, or a related quantitative field
- Demonstrable experience with forecasting, machine learning, and deep learning techniques
- Strong programming skills in Python, including pandas and PyTorch
- Experience running research or data workloads on distributed or cloud compute (AWS preferred)
- Strong grounding in time-series analysis and experiment design, with discipline to avoid overfitting
- Creative, self-motivated, and intellectually curious, with precise communication skills and a desire to work in a small, collaborative, fast-paced team
- Proven experience developing successful quantitative trading strategies is preferred, though not required
- Experience with SQL or time-series databases, C++, and commodities or energy markets is a plus
Compensation & Benefits
- Equal opportunity employer.
Location