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.

Responsibilities:

Daily Fundamentals Reporting

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)

Modeling & Analytics

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

Cross-Functional Support

Collaborate with traders to understand evolving information needs and adjust reporting/modeling priorities accordingly

Support ad hoc analysis requests tied to specific trading opportunities, contract structuring, or market events

Document methodologies and maintain clear version control across reporting and modeling tools

Qualifications:

Required

Bachelor's degree in Business, Finance, Economics, Mathematics, or a related quantitative field, preferably a May 2028 grad.

Working knowledge of SQL and Python or similar language for data analysis

Demonstrated interest in commodity markets, trading, or energy fundamentals (coursework, internships, trading simulations/competitions, or independent projects)

Excellent attention to detail and ability to manage recurring deliverables under time pressure

Strong written and verbal communication skills; ability to translate technical analysis for a trading audience

WhiteWater does not offer housing. Position is required to be in-office at our Austin location

Preferred

Prior completion of WWM's Data Science Internship, or equivalent internship experience in energy trading, fundamentals, or data analytics

Master's degree in Business, Finance, Economics, Mathematics, or a related quantitative field

Experience with data visualization tools (Power BI, Tableau)

Prior exposure to natural gas or broader energy markets

Experience with trading simulations, mock portfolios, or derivatives strategy

Ability to think critically and explain technical work to other colleagues

What Success Looks Like in the First Year :

Fully owns and continuously improves the daily fundamentals reporting suite, with traders relying on it as a core input to daily decision-making

Has contributed meaningfully to at least one modeling initiative alongside the Data Scientist/Strategist that has been incorporated into trading discussions

Demonstrates growing fluency in natural gas market structure, pipeline mechanics, and the specific basins/systems relevant to the desk's positions