2 publicaciones de empleo destacadas de machine learning researcher phd en ciudad de méxico (¡Están contratando!)

Machine Learning Researcher (PhD) - Systematic Commodities Hedge Fund
Moreton Capital Partners —Ciudad de México, CDMX
- $900,000 a $1,700,000 por año
- Tiempo completo
- Doctorado
- Experiencia en construcción
- Python
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Immediate Start - Quant Researcher - Systematic Commodities Hedge Fund
Moreton Capital Partners —Ciudad de México, CDMX
- Tiempo completo
- Doctorado
- Informática
- Maestría
- Vacaciones adicionales o permisos con goce de sueldo
- Seguro de vida
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Machine Learning Researcher (PhD) - Systematic Commodities Hedge Fund
Moreton Capital Partners —Ciudad de México, CDMX
We trade global commodity futures using machine learning, alternative data, and institutional-grade portfolio construction.
$900,000 a $1,700,000 por año
Postulación rápida
Immediate Start - Quant Researcher - Systematic Commodities Hedge Fund
Moreton Capital Partners —Ciudad de México, CDMX
Strong background in machine learning and statistical modelling (tree-based models, regularization, time-series ML).
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Machine Learning Researcher (PhD) - Systematic Commodities Hedge Fund

Moreton Capital Partners
Ciudad de México, CDMX

Postulación rápida

Información del empleo

Tiempo completo
$900,000 a $1,700,000 por año

Cualificaciones

Estadísticas
Doctorado
Estimación y pronóstico
Experiencia en construcción
Python

Descripción completa del empleo

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)

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machine learning researcher phd empleos en ciudad de méxico

Machine Learning Researcher (PhD) - Systematic Commodities Hedge Fund

Immediate Start - Quant Researcher - Systematic Commodities Hedge Fund

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