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Google Internship Data Science Jobs in Georgia (NOW HIRING)

Data Architect

Atlanta, GA ยท On-site

$62.25 - $80/hr

Advanced Analytics/Data Scientists tools: * Must Have: Google Analytics, FireBase, RStudio Server, PyCharm * Programming Languages: * Must Have: SQL, JavaScript, * Agile tools: * Must Have: Azure ...

Data Architect

Warner Robins, GA ยท On-site

$86.80 - $198/hr

Master's degree in Computer Science, Data Science, or Information Technology * AWS, Microsoft, or Google Data Engineering certifications * Certified Data Management Professional (CDMP) or The Open ...

AI & GenAI Data Scientist-Director

Atlanta, GA ยท On-site

$155K - $410K/yr

... Science/Information Systems, Engineering - At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft ...

This 12-week Internship Program (May 18-Aug 7, 2026) is a gateway to full-time career paths for ... Partner in development of scalable solutions using large datasets with other data scientists on the ...

Azure Data Engineer

Atlanta, GA ยท On-site

$110K - $132K/yr

Advanced Analytics/Data Scientists tools: * Must Have: Google Analytics, FireBase, RStudio Server, PyCharm * Programming Languages: * Must Have: SQL, JavaScript, * Agile tools: * Must Have: Azure ...

Data Engineer - GCP

Atlanta, GA ยท On-site +1

$110K - $132K/yr

Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree is a plus. * 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud ...

Data Architect

Atlanta, GA ยท On-site

$61.25 - $78.75/hr

Advanced Analytics/Data Scientists tools: * Must Have: Google Analytics, FireBase, RStudio Server, PyCharm * Programming Languages: * Must Have: SQL, JavaScript, * Agile tools: * Must Have: Azure ...

Bachelor's degree in Computer Science, Computer Engineering, Computer Information Systems, Data ... Position reports to the Google Atlanta, GA office & may allow for a hybrid schedule as per Google ...

Data Engineer - GCP

Atlanta, GA ยท On-site +1

$110K - $132K/yr

Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree is a plus. * 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud ...

Showing results 41-60

Google Internship Data Science information

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 does a data science intern 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.

What cities in Georgia are hiring for Google Internship Data Science jobs? Cities in Georgia with the most Google Internship Data Science job openings:
Infographic showing various Google Internship Data Science job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Data Architect

ACI Infotech

Atlanta, GA โ€ข On-site

$62.25 - $80/hr

Full-time

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Role: Data Architect
Location: Atlanta, GA
Role: Full Time
Mode: On-Site
Accepting H1B Transfer cases
This role is a hands-on technical SME opportunity who will be designing software and services at scale and deliver creative, compelling solutions in the cloud that are cost-effective, reliable, and stable to build Business insight derivation applications on Marketing data sets.
Work Experience/ Education: (Required work experience and education / preferred experience and education that is beneficial to the role. Work experience can include management experience or any functional expertise where proficiency is necessary to be successful in the role)
Work Experience:
    • Minimum 6 years of experience working in IT department with Data & Analytics responsibilities
    • 2+ years of hands-on programming experience (SQL, Python, Scala, Java, etc.,)
    • Recent 2+ years of experience working as Sr. Data Architect on Azure Cloud Platforms

Work Experience: (continued)
    • 1+ years of experience working on Data and Analytics projects in support of Marketing/Loyalty/Digital Customer Experience Use Cases
    • 2+ years of experience working with Google Analytics
    • 1+ years of experience working or at least exposure on any Customer Data Platform (e.g. Microsoft CI, Segment, Tealium, Treasure Data, Informatica, Exponea, SalesForce CDP, etc.,)
    • Experience working on Data & Analytics projects using Agile methodologies
    • Previous Retail, Convenience Store/Petroleum industry experience a plus
    • Previous experience working with Punchh Loyalty platform data is a huge plus

Education:
    • Masters or Bachelor's degree in Computer Science or Information technology with specialization in Data & Analytics, Data Science, Data Engineering or related fields.
    • Any one of the generic Cloud Platform certifications (AWS, Azure, GCP, etc.,)
    • Any one of the Data & Analytics certifications (Azure Fundamentals AZ-900, DP-200: Implementing an Azure Data Solution, DP-201: Designing an Azure Data Solution, DP-203: Data Engineering on Microsoft Azure, etc.,)

Technical Skills, tools:
  • Azure Cloud technologies:
    • Must Have: ADLS Gen2, Azure Data Factory, Azure Databricks, Synapse Analytics,

Azure DevOps:-Boards, Repos, Pipelines, Test Plans
  • Databases:
    • Must Have: SQL servers/SQL databases, MongoDB,
  • BI Platforms:
    • Must Have: Power BI, Power BI Premium,
  • Other MS tools:
    • Must Have: SSMS, SSIS, Visual Studio
  • Advanced Analytics/Data Scientists tools:
    • Must Have: Google Analytics, FireBase, RStudio Server, PyCharm
  • Programming Languages:
    • Must Have: SQL, JavaScript,
  • Agile tools:
    • Must Have: Azure DevOps,