Machine Learning Researcher - Systematic Commodities Hedge Fund

Moreton Capital Partners; Ciudad de México; Presencial; MXN 900.000 - 1.500.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Relocation package to Mexico City

Health and life insurance

Year-end bonus

Generous paid time off

Competitive compensation

Descripción de la vacante

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.

This role targets an applied ML specialist with several years of experience turning ideas into production signals. You will work directly with the CIO and the quant research team to ship models into live trading systems that impact portfolio returns.

Formación

• Several years of applied machine learning experience in industry or a production-oriented research environment.
• Strong Python skills and scientific computing stacks.
• Deep understanding of statistical learning and model validation.
• Experience with large datasets and experimental pipelines.
• Ability to move from theory to practical implementation.
• Intellectual curiosity and strong problem-solving mindset.

Responsabilidades

• Design predictive models for cross-sectional and time-series commodity returns.
• Develop features from price, weather, satellite, macro, and alternative datasets.
• 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.
• Collaborate with engineers to deploy models into live trading systems.

Conocimientos

Python

Time-series modeling

Feature engineering

Model validation

Research mindset

Big data

Educación

PhD in ML or related field

Herramientas

LightGBM

XGBoost

scikit-learn

Pandas

NumPy

TensorFlow/PyTorch

Descripción del empleo

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

• 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

• 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.