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Google Internship Data Science Jobs in Remote, OR

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Desirable but not required certifications include Google Professional Machine Learning Engineer ...

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Desirable but not required certifications include Google Professional Machine Learning Engineer ...

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Desirable but not required certifications include Google Professional Machine Learning Engineer ...

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Senior Business Analyst

OR · Remote

$94K - $122K/yr

... data * Serve as a thought leader for technical business processes, developing forward-thinking ... Bachelor's degree in IT, Computer Science, Management Information Systems, Finance, Accounting, or ...

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Be Seen First

Senior Business Analyst

OR · Remote

$94K - $122K/yr

... data * Serve as a thought leader for technical business processes, developing forward-thinking ... Bachelor's degree in IT, Computer Science, Management Information Systems, Finance, Accounting, or ...

New

Google Internship Data Science information

See Remote, OR salary details

$12

$22

$42

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

As of Jul 15, 2026, the average hourly pay for google internship data science in Remote, OR is $22.48, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.47 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.

What job categories do people searching Google Internship Data Science jobs in Remote, OR look for? The top searched job categories for Google Internship Data Science jobs in Remote, OR are:
What cities near Remote, OR are hiring for Google Internship Data Science jobs? Cities near Remote, OR with the most Google Internship Data Science job openings:
Infographic showing various Google Internship Data Science job openings in Remote, OR as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,763 per year, or $22.5 per hour.
Senior Data Scientist

Senior Data Scientist

SOSi

OR • On-site, Remote

Full-time

Re-posted 28 days ago


Job description

Company Description
Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.
Job Description
SOSi is seeking a Senior Data Scientist to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.
Essential Job Duties:
  • The contractor shall design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes.
  • The contractor shall conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies.
  • The contractor shall submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance.
  • The contractor shall implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements.
  • The contractor shall provide a Rough Order of Magnitude (ROM) Estimate Report before each analytics project, detailing expected Full-Time Equivalent (FTE) hours, compute costs, storage consumption, and infrastructure requirements.
  • The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.

Qualifications
  • Active TS/SCI Clearance.
  • Master's degree in Data Science, Machine Learning, Statistics, or a related field, or;
    • nine (9) years of equivalent experience in AI/ML model development and deployment.
  • Personnel must have demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn, integrating models into production environments, and optimizing performance for real-time analytics.
  • Experience with Databricks, Apache Spark, or similar distributed data processing frameworks is required.
  • Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications.
  • Possess the knowledge and capability to develop advanced machine learning models and optimize analytic workflows for predictive and prescriptive intelligence.
  • Proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and feature engineering.
  • Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications is required.
  • Personnel must be able to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data.

Preferred Qualifications:
  • Desirable but not required certifications include Google Professional Machine Learning Engineer, Microsoft Certified: Azure Data Scientist Associate, or TensorFlow Developer Certification.

Additional Information
Work Environment
  • Full remote flexibility.

Working at SOSi
All interested individuals will receive consideration and will not be discriminated against for any reason.