Posting record
Open 10+ days
- Moreton Capital Partners' site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Moreton Capital Partners, so its true age is longer.
Last checked Nov 1, 2026.
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- Bachelor's degree asked for
What the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
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Skills mentioned
About the role
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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