Machine Learning Researcher - Systematic Commodities Hedge Fund

Moreton Capital Partners is seeking a Machine Learning Researcher to join our team. We are live trading across global commodity futures, supported by an investment process rooted in machine learning.

We trade global 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 an applied ML specialist with several years of experience building and shipping models. A PhD is a plus, not required. You will work directly with the CIO and sit alongside the quant research team to turn ML ideas into live trading signals. 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 and improving features from price, weather, satellite, cash pricing, 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

Requirements

Several years of applied machine learning experience in industry or a similarly production-oriented research environment

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

PhD in Machine Learning, Statistics, Applied Mathematics, Computer Science, Physics, Engineering, or a related quantitative field

Experience with financial markets or systematic trading

Familiarity with time-series modelling or forecasting

Experience with LightGBM/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

Attractive compensation: Highly competitive base salary and annual bonus that scales as the business grows.

Relocation package to our Mexico City office, along with a competitive benefits offering that includes health and life insurance, a year-end bonus, and generous paid time off.

Positive, inclusive and encouraging work environment.

Close collaboration across a global team.