Quant Researcher - Systematic Commodities Hedge Fund

Moreton Capital Partners is seeking a talented Quant Researcher 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.

• 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

• Masters or PhD in either Statistics, Economics, Computer Science
• Strong background in machine learning and statistical modelling (tree‑based models, regularization, time‑series ML)
• Proficiency in Python (pandas, Num Py, scikit‑learn, XGboost, PyTorch/Tensor Flow)
• 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

• 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 optimization, risk parity, or Bayesian model averaging
• Publications, Kaggle competitions, or research track record demonstrating applied ML excellence

• Direct impact:
  Your alphas will go live into production portfolios, with real capital behind them
• Research‑first culture:
  We value deep thinking, novel approaches, and systematic rigor
• Close collaboration across a global team
• Career growth:
  Clear trajectory to senior researcher roles as we scale AUM and expand product lines
• Attractive compensation:
  Highly competitive base salary and annual bonus that scales as the business grows
• Positive, inclusive and encouraging work environment