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Internship Nhl Data Science Jobs (NOW HIRING)

Fervo Energy

Data Science Internship

Houston, TX · On-site

Description Internship Overview You won't be running coffee orders or shuffling paperwork this ... As a Data Scientist Intern, you'll join Fervo's Data Science team to help build models and analyses ...

Gallo

Geospatial Data Science Internship 2027

Modesto, CA · On-site

$26.50 - $27.50/hr

S. - Barefoot Wine & High Noon and are the official sponsors of the NFL, NHL, UFC, and PGA of ... A Taste of What You'll Do Join our team as a GIS (Geospatial Data Science) and be at the forefront ...

Gallo

Geospatial Data Science Internship 2027

Modesto, CA · On-site

$26.50 - $27.50/hr

S. - Barefoot Wine & High Noon and are the official sponsors of the NFL, NHL, UFC, and PGA of ... A Taste of What You'll Do ​ Join our team as a GIS (Geospatial Data Science) and be at the ...

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Athena LLC

Interns leave with a strong understanding of industry-standard data science practices and potential references for your career.

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How much do internship nhl data science jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for internship nhl data science in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is an internship NHL data science?

Internship NHL Data Science positions are temporary roles designed for students or recent graduates to work with the National Hockey League’s data science teams. These internships typically involve analyzing hockey-related data, building predictive models, and assisting with projects that help teams or the league make data-driven decisions. Interns gain hands-on experience with statistical analysis, machine learning, and sports analytics software. The goal is to support the NHL’s efforts to enhance player performance, fan engagement, and overall business strategies using data.

What types of projects do NHL data science interns typically work on?

As a data science intern at the NHL, you can expect to work on projects that involve analyzing player performance data, developing predictive models, and assisting with the visualization of hockey statistics for various stakeholders. Interns often collaborate with full-time data scientists, engineers, and other departments such as scouting or marketing to support ongoing research and new initiatives. The work environment is fast-paced and team-oriented, offering exposure to real-world sports analytics and opportunities to contribute to meaningful projects that impact decision-making within the league.

What are the key skills and qualifications needed to thrive as an NHL data science intern?

To thrive as an NHL Data Science Intern, you need a solid background in statistics, programming (often Python or R), and data analysis, typically gained through coursework or a related degree in fields like computer science, mathematics, or statistics. Familiarity with data visualization tools (such as Tableau or Power BI), machine learning libraries, and databases (like SQL) is commonly required. Strong problem-solving abilities, attention to detail, and effective communication help interns translate complex data into actionable insights for hockey operations or business strategy. These skills are crucial for delivering valuable analyses, supporting data-driven decisions, and effectively communicating findings in the fast-paced sports analytics environment.
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Internship Nhl Data Science jobs near you
Infographic showing various Internship Nhl Data Science job openings in the United States as of September 2026, with employment types broken down into 40% Full Time, and 60% Part Time. Highlights an 40% In-person, and 60% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Data Science Internship

Houston, TX • On-site

Fervo Energy
Clean Energy Semiconductors Manufacturing • 11 - 50 employees
Learn more about Fervo Energyexternal

Full-time, Internship

Posted 6 days ago

Job description

Description

Internship Overview 


You won't be running coffee orders or shuffling paperwork this summer. At Fervo, interns are handed something real: a project of your own, scoped with your manager on day one and yours to drive for the full 12 weeks. You'll work side-by-side with the teams building the next generation of geothermal energy, tackling problems that genuinely move the business forward. At the end of the summer, you'll present your work to our executive leadership team, department leads, and fellow interns, sharing real results with a real audience. This is a real seat at the table - and a real shot at what comes next. 


Position Description


Fervo Energy is developing next-generation geothermal power to deliver firm, carbon-free energy at scale, anchored by our flagship Cape Station development in Milford, Utah. As a Data Scientist Intern, you'll join Fervo's Data Science team to help build models and analyses that turn data into decisions across the business. 

You'll work alongside engineers and data scientists to explore datasets, build predictive models, and translate findings into insights that inform real decisions across drilling, operations, and commercial teams. 

Requirements

 Responsibilities 

  • Explore and analyze datasets to identify trends and opportunities 
  • Build and validate predictive models and statistical analyses 
  • Support development of machine learning models for real-world business problems 
  • Communicate findings and recommendations to technical and non-technical stakeholders 

Required Qualifications 

  • Master's or PhD candidate wrapping up within the next year - we're building a pipeline toward full-time offers 
  • Pursuing a degree in Data Science, Statistics, Computer Science, or a related quantitative field 
  • Strong written and verbal communication skills, including comfort presenting to stakeholders and leadership 
  • Eagerness to learn, take initiative, and adapt quickly to new challenges 
  • Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn) 

Preferred Qualifications 

  • Experience with machine learning frameworks (e.g., PyTorch, TensorFlow) 
  • Familiarity with SQL and data visualization tools 
  • Interest in applying data science to energy or industrial problems 

Apply