# Machine Learning Researcher (PhD) - Systematic Commodities Hedge Fund

> Moreton Capital Partners · Mexico City, Mexico · Full-time · Posted 2026-05-29

**Salary:** MXN 900,000–1,700,000

**Workplace:** on_site

## Description

### Machine Learning Researcher (PhD) – Systematic Commodities Hedge Fund

Moreton Capital Partners is seeking a Machine Learning Researcher to help design and improve the predictive models that power our systematic commodities trading strategies.

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 candidates completing or having recently completed a PhD with a strong machine learning, statistics, or applied mathematics focus who want to apply advanced research in a real capital environment.

You will work directly with the CIO and quant research team to turn cutting-edge ML ideas into live trading signals.

This is not a purely academic role.  
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 new features from price, positioning, options, 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

-   PhD (completed or near completion) in Machine Learning, Statistics, Applied Mathematics, Computer Science, Physics, Engineering, or related quantitative field

-   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 Points For

-   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
-   Performance bonus tied to firm growth and personal performance (up to 3x salary)

## Apply

[Apply at Moreton Capital Partners](https://apply.workable.com/moreton-capital-partners/j/D4C75EB103/apply)

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