Description Machine Learning Researcher (Ph D) – Systematic Commodities Hedge Fund
Moreton Capital Partners is seeking a Machine Learning Researcher to help design and improve the predictive models that power our systematic commodities trading strategies. We trade general commodity futures using machine learning, alternative data, and institutional-grade portfolio construction. Our edge comes from research depth, disciplined experimentation, and robust production systems. This role is for candidates completing or having recently completed a Ph D with a strong machine learning, statistics, or applied mathematics focus who want to apply advanced research in a real capital environment. You will work directly with the CIO and quant research team to turn cutting-edge ML ideas into live trading signals. This is not a purely academic role. Your research will ship to production and directly impact portfolio returns.
What you will work on
Designing predictive models for cross-sectional and time-series commodity returns Developing new features from price, positioning, options, macro, and alternative datasets Improving signal robustness and reducing overfitting through rigorous validation Combining and blending multiple models into portfolio-level forecasts Regime detection, meta-models, and adaptive allocation frameworks Model diagnostics, explainability, and stability analysis Translating research ideas into production-ready implementations Collaborating with engineers to deploy models into live trading systems
Key Responsibilities
Formulate research hypotheses and test them using clean, time-aware ML pipelines Build and evaluate models (tree-based, linear, ensemble, deep learning, etc.)



Run walk-forward and out-of-sample experiments with realistic costs Analyze information coefficients, turnover, drawdowns, and risk-adjusted returns Design feature engineering frameworks and reusable research tooling Document findings clearly and communicate results to portfolio managers Contribute to improving research standards, reproducibility, and processes
Requirements Ph D (completed or near completion) in Machine Learning, Statistics, Applied Mathematics, Computer Science, Physics, Engineering, or related quantitative field Strong Python skills and experience with scientific computing stacks Deep understanding of statistical learning and model validation Experience working with large datasets and experimental pipelines Ability to move from theory to practical implementation Intellectual curiosity and strong problem-solving mindset Comfortable working in a fast-paced, high-ownership environment
Bonus Points For
Experience with financial markets or systematic trading Familiarity with time-series modelling or forecasting Experience with Light GBM/XGBoost, deep learning, or ensemble methods Exposure to portfolio construction or risk modelling Experience with cloud or distributed compute environments Published research or strong applied projects
Why this role is unique
Direct impact: your research drives live trading capital Research freedom: explore ideas with fast feedback loops Real-world data: large, messy, multi-source datasets Small team: high ownership and rapid iteration Strong learning curve across ML, markets, and portfolio construction Clear path into Senior Researcher or Portfolio Manager responsibilities
Benefits Market leading benefits High responsibility from day one Performance bonus tied to firm growth and personal performance (up to 3x salary)

📌 Machine learning researcher (phd) - systematic commodities hedge fund (Hidalgo)
🏢 Moreton Capital Partners
📍 Hidalgo