Quant Researcher Intern - Systematic Commodities Hedge Fund

Quant Researcher Intern – Systematic Commodities Hedge Fund Moreton Capital Partners is seeking a talented Quant Researcher Intern to help build the next generation of alpha signals in commodity futures. Our research is grounded in advanced machine learning, robust testing frameworks, and a deep understanding of global commodity markets. This role is central to our mission: you’ll take ownership of designing, testing, and refining predictive models that directly feed into live trading portfolios. Key Responsibilities • Research, prototype, and validate systematic trading signals across commodities using advanced ML methods. • Design and implement rigorous backtests with realistic frictions, walk-forward validation, and robust statistical tests. • Engineer and evaluate novel features from prices, fundamentals, positioning, options data, and alternative datasets (e.g., satellite, weather and global commodity cash pricing). • Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods. • Develop portfolio construction and optimization techniques and analysis tools to be able to enhance performance and track effects on portfolio execution. • Collaborate with developers to transition research into production-ready strategies. Monitor live performance, attribution, and model drift, ensuring continual improvement of the alpha library. Requirements • Bachelors degree in either Statistics, Economics, Computer Science. • Strong background in machine learning and statistical modelling (tree-based models, regularisation, time-series ML). • Proficiency in Python (pandas, NumPy, scikit-learn, XGboost, PyTorch/TensorFlow). • Understanding of time-series forecasting, cross-validation techniques, and avoiding look-ahead bias. • Academic experience in research and proven ability to translate academic work to production code. • Prior exposure to systematic trading or financial modelling. • Ability to design experiments, interpret results, and iterate quickly in a research environment. Bonus points for: • Knowledge of commodities (agriculture, energy, metals) or macro markets. • Experience with feature engineering on non-traditional datasets (options positioning, weather, satellite). • Experience collaborating in version control environments. • Familiarity with portfolio optimisation, risk parity, or Bayesian model averaging. • Publications, Kaggle competitions, or research track record demonstrating applied ML excellence. Benefits • Research-first culture: We value deep thinking, novel approaches, and systematic rigor. • Direct exposure: Work alongside the CIO and senior researchers, with a direct line to decision-making. • Learning curve: Deep exposure to commodity markets, ML research workflows, and institutional-grade trading systems. • Close collaboration: Work alongside the CIO, Head of Quant Research, and Developers in a lean, highly motivated team. Apply tot his job