Moreton Capital Partners

Systematic commodities investment manager using AI

Quant Researcher - Systematic Commodities Hedge Fund

Quantitative ResearchConfirmed live in the last 24 hours

Full-timeMexico City, CDMX, MexicoIn-person

About the Job

Requirements

A Master's or PhD in Statistics, Economics, or Computer Science.
A strong background in machine learning and statistical modeling, including tree-based models, regularization, and time-series machine learning.
Proficiency in Python, pandas, NumPy, scikit-learn, XGBoost, and PyTorch or TensorFlow.
Understanding of time-series forecasting, cross-validation techniques, and avoiding look-ahead bias.
Academic research experience and the ability to translate academic work into production code.
Prior exposure to systematic trading or financial modeling.
Ability to design experiments, interpret results, and iterate quickly in a research environment.

Responsibilities

Research, prototype, and validate systematic trading signals across commodities using advanced machine-learning methods.
Design and implement rigorous backtests with realistic frictions, walk-forward validation, and robust statistical tests.
Engineer, test, and maintain features from prices, fundamentals, positioning, and alternative datasets such as satellite, weather, and global commodity cash-pricing data.
Blend multiple alpha forecasts into meta-models and portfolio signals using ensemble and Bayesian methods.
Develop portfolio construction and optimization techniques and analysis tools 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, and continually improve the alpha library.

Desired Qualifications

Knowledge of commodities, including agriculture or energy, or macro markets.
Experience with feature engineering on non-traditional datasets such as weather or satellite data.
Experience collaborating in version-control environments.
Familiarity with portfolio optimization, risk parity, or Bayesian model averaging.
Publications, Kaggle competitions, or a research track record demonstrating applied machine-learning excellence.

Quant Researcher - Systematic Commodities Hedge Fund

Moreton Capital Partners · Mexico City, Mexico · Full-time · Posted 2026-08-29

Salary: USD 50,000–220,000

Workplace: on_site

Description

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.

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, test, and maintain features from prices, fundamentals, positioning, and alternative datasets (e.g., satellite, weather and global commodity cash pricing). Feature work is a core part of this role.
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) or macro markets.
Experience with feature engineering on non-traditional datasets (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.

Apply

Apply at Moreton Capital Partners

About the Company

Moreton Capital Partners

Systematic commodities investment manager using AI

Moreton Capital Partners runs market-neutral commodity funds using a technology-driven approach that blends agentic AI, large language models, machine learning, and quantitative research to find relative-value opportunities across energy, metals, and agriculture. It processes hundreds of thousands of data points per day—covering supply and demand, market positioning, and volatility—to generate trading signals that guide fund allocations and risk controls in over 100 commodities. The firm differentiates itself with an adaptive, data-rich method that evolves with changing market structure and a team with deep experience in both physical trading and systematic investing, focusing on institutional clients seeking stable returns rather than simple price bets. Its goal is to deliver attractive risk-adjusted returns for institutions by exploiting inefficiencies and weather-related or inflation risks while keeping a market-neutral posture.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Delaware, United States
Founded: Not listed

Recently Posted Jobs

Explore more opportunities at Moreton Capital Partners

See more jobs