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Internship Nhl Data Science Jobs (NOW HIRING)

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 Aug 21, 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 August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Data Science Intern

DEUNA

San Francisco, CA • On-site

Other

Re-posted 23 days ago

Job description

We are looking for curious, analytical, and motivated students who are eager to learn about Data Science in a fast-paced technology environment. During the internship, you will support the Data team by analyzing data, building models, developing insights, and contributing to projects that have a direct impact on our products and business.

This is an educational, unpaid internship designed to provide practical experience, mentorship, and exposure to real-world data science projects.

Key Responsibilities
  • Assist in collecting, cleaning, and preparing datasets for analysis.
  • Perform exploratory data analysis to identify trends and patterns.
  • Support the development and evaluation of machine learning models.
  • Build dashboards and visualizations to communicate business insights.
  • Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives.
  • Document analyses, methodologies, and project findings.
  • Participate in team meetings, knowledge-sharing sessions, and technical discussions.
  • Learn and apply best practices in data science, experimentation, and analytics.
Qualifications Required
  • Currently pursuing a Bachelor’s or Master’s degree in:
    • Computer Science
    • Data Science
    • Statistics
    • Mathematics
    • Engineering
    • Economics
    • Physics
    • Or a related quantitative field.
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