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Open nowPosted 36 days ago

Quant Developer - Systematic Commodities Hedge Fund

Workable (global search)108,016 open roles

Where
Mexico City, CDMX, Mexico
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Your applicationOpen nowQuant Developer - Systematic Commodities Hedge FundWorkable (global search) · Mexico City, CDMX, Mexico

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7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

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  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 36 days ago

Workable (global search) median: 7 days open

The posting

Quant Developer – Systematic Commodities Hedge Fund

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

This is a unique opportunity to work directly with the global team, owning infrastructure that takes research ideas to production in a fast-moving, real capital environment.

Key Responsibilities

  • Build and maintain data pipelines ingesting futures and alternative datasets (from price data from vendor feeds to unstructured data).
  • Build and improve LLM-based workflows that support research, data processing, and internal tooling.
  • Improve backtesting framework (event-driven simulations, realistic slippage/costs, walk-forward validation, portfolio performance analysis).
  • Support research tooling: feature libraries, experiment tracking, artefact storage.
  • Machine learning cloud and local execution and optimization setup.
  • Productionize signals into the live trading stack with CI/CD, monitoring, and version control.
  • Develop dashboards and alerting for data quality, latency, and model drift.
  • Collaborate with researchers to translate hypotheses into robust, testable experiments, as well as enhance proposed process computationally.

Requirements

  • Fluency in Python and SQL; clean, testable code is a must.
  • Experience with data engineering (Airflow, Snowflake, pandas, polars workflows).
  • Prior exposure to systematic trading, backtesting, or market data pipelines.
  • Familiarity with cloud environments (AWS), containers (Docker), and CI/CD.
  • Self-starter with the ability to work autonomously in a lean, high-ownership environment.
  • Bachelors in CS/Comp-Eng or computationally heavy subject matter, and ideally, a minor in Finance.

Bonus points for:

  • Commodities or macro markets exposure.
  • Systematic medium term investment exposure.
  • Experience with ML Ops tools (MLflow, Weights & Biases), feature stores, or model monitoring.
  • Front-end skills (TypeScript/React) to help build researcher dashboards.

Benefits

  • Impact from day one: You’ll be building mission-critical infrastructure for a fund that is already live trading for large institutional investors.
  • Direct exposure: Work alongside the CIO and senior researchers, with a direct line to decision-making.
  • Learning curve: Deep exposure to commodity markets, ML research workflows, and institutional-grade trading systems.
  • Growth trajectory: Clear path to increased scope and compensation as the fund scales with institutional AUM.
  • Attractive compensation: Highly competitive base salary and annual bonus that scales as the business grows.
  • Positive, inclusive and encouraging work environment.
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