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Google Internship Data Science Jobs in Virginia (NOW HIRING)

Experience with AWS, Azure, Google Cloud, or hybrid cloud environments. * Understanding of data ... Bachelors or Masters degree in Data Science, Computer Science, Data Engineering, Mathematics ...

Experience with AWS, Azure, Google Cloud, or hybrid cloud environments. * Understanding of data ... Bachelor's or Master's degree in Data Science, Computer Science, Data Engineering, Mathematics ...

Senior Data Scientist

Chantilly, VA · On-site

$130K - $160K/yr

... or Google Charts * Understanding of relevant statistical measures, development and evaluation of data sets. * Salary Range: $130,000 - $160,000/Year, DOE Skills Required The Senior Data Science ...

Required : • 2+ years of experience in data science in a professional work environment • Experience with machine learning, data mining, statistics, or graph algorithms in academic or internship ...

Position: Senior Data Science Analyst Location: Richmond, VA (1 week in office, 1 week remote ... Cloud platform experience (AWS, Azure, or Google Cloud Platform). * Experience influencing ...

New

Data Scientist

Mclean, VA

$125K - $160K/yr

Stay current with modern data science methodologies, ML techniques, data processing tools, and ... Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google ...

Data Scientist

Mclean, VA

$125K - $160K/yr

Stay current with modern data science methodologies, ML techniques, data processing tools, and ... Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google ...

Senior Data Scientist

Vienna, VA · On-site

$160K - $180K/yr

Provide guidance on best practices and industry standards across data science and analytics, data ... Cloud project work using Google, AWS and/or Azure. * Demonstrated high proficiency in statistical ...

AI and Data Science Engineer III

Rosslyn, VA · On-site

$130K - $156K/yr

As an AI and Data Science Engineer III, you will serve as a technical leader supporting advanced ... Google Cloud Platform (GCP) * Active Top Secret security clearance * Ability to travel 30%, on ...

Data Scientist

Mclean, VA · On-site

$125K - $160K/yr

Stay current with modern data science methodologies, ML techniques, data processing tools, and ... Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google ...

Provide guidance on best practices and industry standards across data science and analytics, data ... Cloud project work using Google, AWS and/or Azure. * Demonstrated high proficiency in statistical ...

Provide guidance on best practices and industry standards across data science and analytics, data ... Cloud project work using Google, AWS and/or Azure. * Demonstrated high proficiency in statistical ...

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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 Virginia are hiring for Google Internship Data Science jobs? Cities in Virginia with the most Google Internship Data Science job openings:
Infographic showing various Google Internship Data Science job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Science

Altagrove LLC

Norfolk, VA • On-site

Full-time

Re-posted 5 days ago


Job description

Salary:

Who we are:


Altagrove delivers smart and innovative technology solutions that create competitive advantages for our customers and their missions. Our focus areas include Space, Connectivity, Cyber, Cloud, Analytics, and Research & Development. As we continue to grow, Altagrove is actively recruiting for a Data Scientist to join our energetic and entrepreneurial team that is executing on a variety of projects that are technology oriented. A successful candidate will bring a core area of expertise and a passion for learning and implementing new ideas in a start-up environment.


Follow us at -https://www.linkedin.com/company/altagrove


What you will do:


  • Design, develop, deploy, and maintain AI-enabled analytics solutions supporting operational and strategic mission objectives.
  • Build and optimize enterprise data pipelines, ingestion frameworks, transformation workflows, and integration services supporting analytics and AI platforms.
  • Develop machine learning models, predictive analytics capabilities, and decision-support solutions using structured and unstructured data.
  • Design and implement Large Language Model (LLM) solutions, Retrieval-Augmented Generation (RAG) architectures, vector databases, and AI-enabled knowledge management capabilities.
  • Develop scalable data architectures, metadata enrichment pipelines, indexing services, and retrieval systems supporting enterprise knowledge exploitation.
  • Collaborate with mission stakeholders, engineers, and technical teams to identify high-value AI and data-driven use cases.
  • Conduct data exploration, feature engineering, model training, validation, testing, and performance optimization activities.
  • Design and implement ETL/ELT processes supporting operational, analytical, and machine learning workloads.
  • Develop dashboards, visualizations, reports, and analytical products that communicate insights to technical and non-technical stakeholders.
  • Support cloud-native and hybrid data environments leveraging AWS, Azure, Kubernetes, and modern data engineering technologies.
  • Implement data quality controls, monitoring solutions, security controls, and governance practices across enterprise data environments.
  • Work closely with Cloud Engineers, DevSecOps Engineers, and Software Developers to support end-to-end solution delivery.
  • Research emerging AI, machine learning, and data engineering technologies and recommend innovative applications for customer missions.
  • Support technical documentation, architecture development, operational procedures, training materials, and knowledge transfer activities.


What you will bring:


  • Experience developing and deploying advanced analytics, machine learning, artificial intelligence, or enterprise data engineering solutions within government, defense, intelligence, or highly regulated environments.
  • Strong proficiency in Python and experience with modern data science and engineering frameworks.
  • Experience with machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, or similar technologies.
  • Experience designing and maintaining enterprise data pipelines, ETL/ELT workflows, and data integration architectures.
  • Familiarity with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), vector databases, embeddings, and prompt engineering concepts.
  • Experience working with SQL, NoSQL, data lakes, data warehouses, and cloud-native data platforms.
  • Experience with AWS, Azure, Google Cloud, or hybrid cloud environments.
  • Understanding of data governance, metadata management, data quality, security, and compliance principles.
  • Experience with containerization technologies, Kubernetes, DevSecOps practices, and Infrastructure-as-Code is highly desirable.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to collaborate effectively across multidisciplinary engineering and mission teams.
  • Experience supporting NATO, DoD, Intelligence Community, or other national security organizations is highly desired.
  • Bachelors or Masters degree in Data Science, Computer Science, Data Engineering, Mathematics, Statistics, Engineering, Information Systems, or a related discipline.
  • Active Secret Clearance required; TS/SCI or NATO Secret preferred.
  • Exceptional attention to detail and organizational skills.