Quant Developer - Systematic Commodities Hedge Fund

Moreton Capital Partners is seeking a talented Quant Developer to join our team at the ground floor of an ambitious build. We are launching 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 ResponsibilitiesBuild and maintain data pipelines ingesting futures, options, and alternative datasets (from price data from Bloomberg and vendor feeds to unstructured data)Improve backtesting framework (event-driven simulations, realistic slippage/costs, walk-forward validation, portfolio performance analysis)Support research tooling: feature libraries, experiment tracking, artefact storageMachine learning cloud and local execution and optimization setupProductionize signals into the live trading stack with CI/CD, monitoring, and version controlDevelop dashboards and alerting for data quality, latency, and model driftCollaborate with researchers to translate hypotheses into robust, testable experiments, as well as enhance proposed process computationallyRequirementsFluency in Python and SQL; clean, testable code is a mustExperience with data engineering (Airflow, Snowflake, pandas, polars workflows)Prior exposure to systematic trading, backtesting, or market data pipelinesFamiliarity with cloud environments (AWS), containers (Docker), and CI/CDSelf-starter with the ability to work autonomously in a lean, high-ownership environmentBachelors in CS/Comp-Eng or computationally heavy subject matter, and ideally, a minor in FinanceBonus points forCommodities or macro markets exposureSystematic medium term investment exposureExperience with ML Ops tools (MLflow, Weights & Biases), feature stores, or model monitoringFront-end skills (TypeScript/React) to help build researcher dashboardsBenefitsImpact from day one: You'll be building mission-critical infrastructure for a fund that begins live trading this year for large institutional investorsDirect exposure: Work alongside the CIO and senior researchers, with a direct line to decision-makingLearning curve: Deep exposure to commodity markets, ML research workflows, and institutional-grade trading systemsGrowth trajectory: Clear path to increased scope and compensation as the fund scales with institutional AUMAttractive compensation: Highly competitive base salary and annual bonus that scales as the business growsPositive, inclusive and encouraging work environment#J-18808-Ljbffr