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Internship Nhl Data Science Jobs (NOW HIRING)

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

Launch your data science or technical analyst career by building AI and analytics solutions that ... Experience through internships, personal projects, research, hackathons, student organizations, or ...

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a ...

This area provides data science support for internal business partners at State Farm, including ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

This area provides data science support for internal business partners at State Farm, including ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

This area provides data science support for internal business partners at State Farm, including ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

This area provides data science support for internal business partners at State Farm, including ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

This area provides data science support for internal business partners at State Farm, including ... Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ...

Centerfield is looking for a curious, hands-on Data Science Intern to work alongside our Data ... This is a builder's internship: you'll write real code, work with real data, and ship work that ...

Data Science Intern

Palo Alto, CA · On-site +1

$28.27 - $60/hr

A passion for applying mathematical models and computer science technology to data-driven decision ... Subject to the terms and conditions of the applicable plans then in effect, full-time interns are ...

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Internship Nhl Data Science information

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

As of Jul 13, 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.

How much do NHL interns make?

NHL data science interns typically earn between $15 and $25 per hour, depending on the organization and location. Internships often last for a few months during the off-season or summer, providing valuable experience with sports analytics tools and data analysis techniques.

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

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, and why are they important?

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.

How much do NHL data scientists make?

NHL data scientists typically earn between $70,000 and $120,000 annually, depending on experience, education, and the level of responsibility. Entry-level roles may start lower, while experienced professionals with advanced skills in data analysis, machine learning, and sports analytics can earn higher salaries. Compensation often includes benefits and opportunities for performance bonuses.

What are Internship NHL Data Science positions?

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.

How much do NFL data scientists make?

NFL data scientists typically earn between $70,000 and $120,000 annually, depending on experience, education, and the organization. They often work with advanced analytics tools and programming languages like Python or R to analyze game data and improve team performance.

How to become an NHL data analyst?

To become an NHL data analyst, candidates typically need a strong background in data science, statistics, or related fields, along with proficiency in programming languages like Python or R and experience with sports analytics tools. Gaining knowledge of hockey-specific data and metrics, as well as understanding game strategies, enhances effectiveness. Internships or entry-level roles in sports analytics can provide practical experience and industry connections.
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Data Science Internship (Data Platforms)

Mitsubishi Heavy Industries Group

Lake Mary, FL • On-site

Other

Posted 3 days ago

New


Job description

Data Science Associate

 

Company Overview

At Mitsubishi Power, we're not just building better clean energy technologies; we're architecting a better future. Our team is boldly redefining power generation to accelerate the world's energy transition. We operate as one team, pushing toward our vision of the future. We value problem solvers, prioritize collaboration, and support each other in an inclusive culture built on accountability and authenticity by demonstrating our values: Safety, Family, Innovative, Inclusive, Accountable & Courageous. Together, we're building the future we all aspire to - making net zero a reality.

Role Overview

The Data Scientist Intern supports Mitsubishi Power's IT Data Platforms team by contributing to data quality, data cataloging, and automation efforts within enterprise data environments. This hands-on internship provides practical experience working with cloud-based data platforms, centralized data repositories, and Microsoft Power Platform tools. The role collaborates with Data Platforms leadership, Enterprise Applications, and IT stakeholders to support scalable, high-quality data solutions used across the business. 

Key Responsibilities

  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.

 

 

Requirements

  • Assist with data quality assessments across enterprise data sources, identifying gaps, inconsistencies, and improvement opportunities.
  • Support data catalog activities including documentation of datasets, metadata, data definitions, and lineage.
  • Validate, organize, and prepare ingested data within centralized platforms such as data lakes and structured repositories.
  • Contribute to automation efforts to surface data into Microsoft Power Apps and Power Automate workflows.
  • Perform data validation and reconciliation to ensure accuracy and completeness between source and ingested data.
  • Assist with development of basic dashboards, reports, and visualizations to support data visibility and usage.
  • Support testing and user acceptance activities to validate data processes and automation solutions.
  • Maintain tracking artifacts such as data quality logs, catalog trackers, and automation inventories.
  • Document data processes, standards, and learnings to support long-term platform sustainability.


Learning Outcomes

  • Gain hands-on experience with enterprise data platforms, including data lakes and cloud-based environments, understanding how data supports business operations.
  • Develop core data skills in data quality, validation, cataloging, and metadata management using real-world datasets.
  • Apply analytics and automation tools such as Excel, SQL, and Microsoft Power Platform to support business processes and workflows.
  • Strengthen problem-solving and communication skills by working cross-functionally and translating data insights into clear, actionable outcomes.

 

Mitsubishi Power is an Equal Employment Opportunity (EEO) employer actively seeking to diversify the workforce and is committed to a policy of equal employment opportunity. Therefore, all qualified applicants regardless of race, color, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally recognized protected basis under applicable law, are strongly encouraged to apply.