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Google Internship Data Science Jobs (NOW HIRING)

Google

Data Engineer, GCS Data Science

New York, NY · On-site

$125K - $150K/yr

Bachelor's degree in Computer Science, a related technical field, or equivalent practical ... Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who ...

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 google internship data science jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for google internship 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 are the key skills and qualifications needed to thrive as a Google Data Science Intern, and why are they important?

To thrive as a Google Data Science Intern, you need a solid background in statistics, programming (such as Python or R), and data analysis, typically supported by current enrollment in a relevant degree program. Familiarity with tools like SQL, TensorFlow, and data visualization platforms is commonly expected, along with experience in machine learning frameworks. Strong problem-solving abilities, effective communication, and collaboration skills help interns contribute meaningfully to cross-functional teams. These skills are essential to analyze complex datasets, deliver actionable insights, and succeed in Google's fast-paced, innovative environment.

What types of projects do Data Science interns typically work on during a Google internship?

Data Science interns at Google often collaborate on high-impact projects alongside full-time data scientists and engineers. Projects may include analyzing large datasets to identify trends, building machine learning models, or developing data-driven solutions for products and services. Interns are encouraged to contribute ideas, participate in code reviews, and present findings to their teams. This hands-on experience allows interns to gain exposure to Google's tools and methodologies, while also building a strong foundation for future roles in data science.

What is a Google Internship in Data Science?

A Google Internship in Data Science is a temporary, paid position where students or recent graduates work with Google's data science teams. Interns are involved in analyzing large datasets, building machine learning models, and providing insights to improve Google products and services. The internship offers hands-on experience, mentorship, and exposure to real-world data science challenges in a leading tech company. Applicants typically need strong analytical skills, proficiency in programming languages like Python or R, and a background in statistics or computer science.

What is the difference between Google Internship Data Science vs Google Data Analyst Internship?

AspectGoogle Internship Data ScienceGoogle Data Analyst Internship
Required SkillsProgramming (Python, R), statistics, machine learning, data modelingData analysis, SQL, Excel, visualization tools
Work EnvironmentCollaborative, research-focused, technical projectsBusiness-oriented, reporting, data interpretation
Industry UsageResearch, product development, machine learning modelsBusiness insights, performance metrics, reporting

Google Internship Data Science roles focus on developing machine learning models and advanced analytics, requiring programming and statistical skills. In contrast, Google Data Analyst Internships emphasize data interpretation, reporting, and visualization for business decisions. Both roles are valuable within Google's data ecosystem but serve different functions based on technical depth and business application.

More about Google Internship Data Science jobs
What cities are hiring for Google Internship Data Science jobs? Cities with the most Google Internship Data Science job openings:
What states have the most Google Internship Data Science jobs? States with the most job openings for Google Internship Data Science jobs include:
What job categories do people searching Google Internship Data Science jobs look for? The top searched job categories for Google Internship Data Science jobs are:
Google Internship Data Science jobs near you
Infographic showing various Google Internship Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Data Science Internship (Data Platforms)

MHI

Lake Mary, FL • On-site

Internship

Posted 21 days ago

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.

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