Intern - Data Science (Summer 2026) bei GTI Energy

GTI Energy is building new initiatives to support significant business growth objectives and build business value well into the next decade through commercialization of technologies and integrated solutions needed in the transition to low-carbon, low-cost energy systems. 

GTI Energy is seeking a Data Science Intern to join our Digital Innovation team to enhance our capabilities in statistics and data science by strengthening and supporting enterprise-wide strategic initiatives. In this role, the Intern will support in the execution of on-going projects and initiatives, including scientific research around development of low-emissions energy systems through data-driven modeling and statistical analysis.

GTI Energy embraces the power of innovation and collaboration to solve consequential energy challenges.  By demonstrating continuous improvements in technology and solutions that lower the emissions and costs of energy, we will shape energy systems that decarbonize economies, protect our environment, and benefit the people they serve. We do this by putting people at the center of everything we do. We support and uplift people, ensuring they have the resources and confidence needed to live as their authentic selves and reach their full potential.

We offer generous benefits, competitive salaries, opportunities for professional growth and career advancement. We prioritize and maintain an inclusive, diverse, and respectful culture, and we ensure reasonable accommodation is made to enable individuals with disabilities to perform the essential functions of their role.

Being part of the GTI Energy team means being surrounded by people that are passionate and purpose driven, empowered to continuously learn, ask hard questions, and leverage their knowledge and experience to drive toward a greater purpose.

The position will be based in the Chicagoland area at the GTI Energy Headquarters. We offer a hybrid/core work week, where employees are remote Mondays and Fridays, and required to be on-site Tuesday through Thursday. While local candidates are preferred, GTI Energy does provide seasonal housing assistance for the right candidate. This position may require some field travel to GTI Energy’s offsite Fort Collins, CO office location as needed.

• Perform exploratory data analyses and apply statistical modeling and machine learning approaches to answer research questions and develop tools to support data-driven decision making
• Scrape and wrangle data from open-source repositories
• Create data visualizations and dashboards to communicate insights and findings to stakeholders
• Develop presentations and written reports to communicate findings
• Develop unique approaches to investigating key research questions, including leading programs related to methane emissions mitigation, digitalization in energy, and net zero energy systems
• Support ongoing research efforts using a disciplined approach and standard best practices
• Participate in 1-on-1 and team meetings and contribute to team projects
• Participate in GTI Energy Digital Innovation team building and networking events
• Perform other duties as assigned

• Currently enrolled in or completed within the last year a Bachelor or Master’s degree program in computer science, data science, statistics, mathematics or related field
• GIS experience is a plus
• Experience demonstrating ability to communicate technical statistical/analytical concepts a plus
• Experience using data visualization techniques and programming libraries (e.g., scatterplots, boxplots, ggplot2, pandas, matplotlib)

• Ability to wrangle and process data using programming libraries (e.g., tidyverse, pandas)
• Policy and Regulation knowledge related to energy is a plus
• Familiarity with/interest in environmental justice
• Familiarity with and ability to implement basic statistical analyses and concepts, such as t-tests, linear regression, hypothesis testing, and confidence intervals, and machine learning techniques, such as classification, clustering, and predictive modeling
• Familiarity with advanced statistical methods such as Bayesian analysis, time-series or spatial analyses, or survey statistics a plus
• General knowledge of the energy industry, particularly related to the natural gas supply chain (including emissions management), hydrogen, energy efficiency, or engineering methods
• Excellent problem-solving skills and ability to work independently
• Strong written and oral communication
• Ability to work collaboratively on teams with both technical and non-technical members
• Strong organizational and time management skills with excellent attention to detail
• An ability to translate technical information into a format that is understandable and valuable to non-technical audiences
• Strong programming skills, preferably in R, Python, or similar software
• Willingness to learn new analytical techniques and data science methods

The pay range for this position is $17 - $28 USD per hour. This pay range is GTI Energy’s good faith estimate, and the actual pay may vary based on a number of factors including, but not limited to, GTI Energy’s business or organizational needs and an individual’s relevant experience, education, qualifications, certifications, skills, seniority, geographic location, and/or performance. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus. The range listed is just one component of GTI Energy’s total compensation package for employees. Other rewards may include annual bonuses, paid time off, and region-specific benefits.

GTI Energy is committed to developing a barrier-free recruitment process and work environment.  If you require any accommodation, please e-mail us at [email protected] and we’ll work with you to meet your accessibility needs. You must have legal authorization to work for GTI Energy on your date of hire with no further action required by GTI Energy. We are an Equal Employment Opportunity employer and give consideration to qualified applicants without regard to race, color, age, religion, sexual orientation, gender identity, national origin, disability, veteran status, pregnancy, or genetic information.