Quant Developer Intern - Systematic Commodities Hedge Fund at Moreton Capital Partners

, , United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Data Engineering, Airflow, Snowflake, Pandas, Polars, Machine Learning, Cloud Environments, AWS, Docker, CI/CD, Backtesting, Systematic Trading, Feature Libraries, Dashboards, Alerting

Industry

Investment Management

Description

Quant Developer Intern – Systematic Commodities Hedge Fund Moreton Capital Partners is seeking a talented Quant Developer Intern 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 CIO and Head of Quant Research, owning infrastructure that takes research ideas to production in a fast-moving, real capital environment. Key Responsibilities Build 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 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. 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. Impact from day one: You’ll be building mission-critical infrastructure for a fund that begins live trading this year 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.

Responsibilities

Build and maintain data pipelines for futures and options, and improve the backtesting framework. Collaborate with researchers to translate hypotheses into robust experiments and productionize signals into the live trading stack.