Commodities Quantitative Research Extern (Machine Learning)

Location: Houston, Texas, United States

Company

hirify.global operates investment teams focused on commodity markets and data-driven trading research.

What you will do

• Conduct independent, project-based quantitative research on commodity markets using large and complex datasets.
• Develop market hypotheses and evaluate them through statistical analysis, modeling, and back testing.
• Build quantitative models for forecasting, market-dynamics analysis, trading opportunities, and risk assessment.
• Apply statistical, econometric, machine learning, stochastic modeling, derivatives, and time-series techniques.
• Evaluate alternative datasets, engineer features, and translate research into reproducible code, analytical tools, and dashboards.
• Present research findings and model results to Portfolio Managers, traders, analysts, and other investment professionals.

Requirements

• Eligibility as a student enrolled at Rice University is required.
• Current enrollment in a bachelor's, master's, or PhD program in a quantitative discipline such as mathematics, statistics, computer science, engineering, physics, or economics.
• Strong foundations in probability, statistics, and statistical modeling, with rigorous problem-solving and analytical skills.
• Experience working with real-world datasets, including noise, missing data, overfitting, model assumptions, and out-of-sample testing.
• Programming experience in Python and experience with SQL, Python data tools, and/or Microsoft Excel.
• Ability to investigate open-ended research questions independently and communicate complex quantitative ideas clearly.

Nice to have

• Experience with C++, R, or similar programming languages.
• Familiarity with optimization, machine learning, econometrics, time-series analysis, stochastic modeling, or derivatives.
• Previous experience in finance, commodities, or energy markets.

Culture & Benefits

• Direct collaboration with Portfolio Managers, traders, and analysts.
• Project-oriented work with ownership from initial research idea through analysis, back testing, and presentation.
• Exposure to crude oil, refined products, natural gas, power, and related physical and financial markets.
• Fast-paced, performance-oriented environment emphasizing intellectual curiosity, analytical rigor, collaboration, and ownership.