Internship Starbucks Data Analytics Jobs in Spring, TX

Commodity Trading Analytics Internship Program

Six-Month Internship: June 15 - December 16, 2027
Houston and NYC (full-time, on site)

Salary Range: $68,000 - $100,000 annualised

Engelhart's Internship Program offers a unique opportunity to gain hands-on experience with North American Front Office teams working at the intersection of commodities markets, data, analytics, modelling and trading. Interns will contribute to practical, data-led projects that support commercial decision-making, forecasting, risk analysis and market insight across power, gas, and broader commodity markets. To be eligible for consideration, applicants must have the right to work in the United States for the full duration of the internship and be available to commence their six-month internship on site from June 15, 2027.

The internship opportunities covered by this advert are as follows:

• Quantitative Development Intern, Houston
• Quantitative Research Intern, Houston
• NA Power & Gas Analytics Intern, Houston
• FTR Analytics Intern, Houston
• NA Structured Products & Origination Analytics Intern, Houston
• West Power Analytics Intern, New York

Applicants may indicate areas of particular interest during the process. All roles require strong analytical and technical skills, with opportunities spanning data analysis and visualisation, machine learning, forecasting, financial modelling, statistics/econometrics and quantitative modelling. Final allocation will take into account business need, candidate profile and overall fit.

What You Can Expect

• Hands-on experience on a commodities trading desk, working on analytical projects with real commercial relevance.
• Exposure to how data, analytics, visualisation, forecasting, machine learning and modelling support trading and commercial decisions across North American power, gas and broader commodity markets.
• Close learning and mentorship from experienced front office professionals, including direct exposure to desk leadership.
• A structured six-month internship within a global commodities business, combining cohort-based learning with deep desk integration.

Example Project Areas

Depending on the internship opportunity, projects may include data analysis and visualisation, building models and analytics, improving machine learning models for power prices, gas demand or renewables, working on Monte Carlo simulations and time-series analysis, supporting pricing, valuation, optimisation or portfolio construction problems, developing AI-enabled tools, improving pre-trade pricing or portfolio management of structured origination positions, and producing insights that help inform front office trading and commercial decisions.

Key Responsibilities

• Work closely with a Houston or New York front office team on data-led projects within North American power and gas, FTR, structured products and origination, or West Power.
• Analyse large market, trading and fundamental datasets to identify insights that support forecasting, valuation, risk analysis and commercial decision-making.
• Develop, test or improve analytical tools, models, dashboards or workflows using Python and other relevant tools.
• Support forecasting, financial modelling, machine learning, statistical/econometric analysis, Monte Carlo simulation or quantitative optimisation activities, depending on desk requirements.
• Conduct market research and present findings clearly to technical and commercial stakeholders.
• Contribute to day-to-day desk activity, building practical understanding of how analytics supports trading and portfolio decisions.

About You

Across our 2027 internship program, we are looking for motivated, intellectually curious individuals who are keen to apply strong analytical, quantitative and technical skills to real business challenges in power, gas, renewables and broader commodity markets. You should be comfortable working with data, learning quickly, and collaborating closely with front office teams in a fast-paced trading environment.

The following experiences and skills are essential for application:

• Strong academic background in a quantitative discipline such as Computer Science, Data Science, Engineering, Physics, Mathematics, Statistics, Economics, Finance or a related STEM field.
• Strong Python skills, with the ability to analyze, manipulate and interpret complex data sets.
• Excellent analytical and problem-solving skills, with a structured and detail-oriented approach.
• Evidence of applying data analysis, coding or quantitative methods to a practical problem, gained through academic projects, internships, research, personal projects or other relevant experience.
• Demonstrable interest in commodities, power or financial markets, including an ability to discuss relevant market developments, gained through academic study, projects, internships, research or personal interest.
• Business-level English proficiency.
• Right to work in the United States for the full duration of the internship.
• Effective communication skills and a collaborative mindset, with the confidence to work closely with commercial and technical stakeholders.
• Intellectual curiosity, with the motivation to understand how market fundamentals, data and commercial decisions interact.

The following would be advantageous:

• Experience with SQL, relational databases, data visualisation, machine learning, AI/LLM tools, Git, financial modelling, advanced Excel/VBA, or working with large market
• Exposure to forecasting models, valuation, statistics/econometrics, time-series analysis, stochastic modelling, Monte Carlo simulation, optimisation, MILPs or portfolio construction.