Data Science Intern - Summer 2027

WWM Logistics, LLC is seeking a Data Science Intern to support its natural gas trading desk.

This role sits at the intersection of daily market reporting and deeper quantitative analysis, providing traders with the timely fundamental data they need to evaluate supply and demand, while also partnering with the Data Scientist and Strategist on model development aimed at generating trading signals.

This is an ideal opportunity for a detail-oriented, quantitatively skilled early-career professional looking to build a career in commodity trading and market analytics.

This role is the natural next step for graduates of WWM's Natural Gas Analyst / Data Science Internship.

Completion of the internship is valued but not required – we also hire directly into this role.

• Build, maintain, and deliver standardized daily reports summarizing natural gas supply and demand fundamentals (production, storage, weather-driven demand, pipeline flows, rig counts) used directly by traders to inform positioning
• Own the rollout of these standardized reports and monitor them on an ongoing basis, troubleshooting data issues and refining processes to reduce manual turnaround time and improve reliability
• Monitor and flag material shifts in fundamental data that could influence price movement, escalating findings to traders and senior analysts in real time
• Maintain data integrity across multiple third-party and internal data sources (e.g., EIA, pipeline bulletin boards, weather services, production estimates)

• Partner with the Data Scientist and Strategist to develop and refine quantitative models aimed at identifying trading signals from fundamental and market data
• Support back-testing and validation of new analytical approaches, helping translate research into production-ready tools
• Assist in building supply/demand balance models and scenario analyses across key basins and pipeline systems
• Contribute to the automation and scaling of data pipelines that feed both daily reporting and longer-term research projects