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