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Google Internship Data Science Jobs in Remote, OR

SOSi

Senior Data Scientist

Myrtle Point, 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 ...

SOSi

Senior Data Scientist

OR · On-site +1

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 ...

SOSi

Senior Data Scientist

OR · On-site

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 ...

LEARN COLLABORATE INC

Be Seen First

Startup Operations & Investor Relations Intern ($800 Monthly Stipend)

OR · Remote

$1K/yr

Maintain, clean, and track investor data and pipeline interactions within HubSpot . * Investor ... Coordinate outreach materials, follow-ups, and documentation logistics using Google Drive . * Team ...

LEARN COLLABORATE INC

Be Seen First

Startup Operations & Investor Relations Intern ($800 Monthly Stipend)

OR · Remote

$1K/yr

Maintain, clean, and track investor data and pipeline interactions within HubSpot . * Investor ... Coordinate outreach materials, follow-ups, and documentation logistics using Google Drive . * Team ...

All JobsGoogle Internship Data Science JobsGoogle Internship Data Science Jobs in Remote, OR

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 Jun 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.

Can I get a job in Google as a data scientist?

A data scientist internship at Google provides valuable experience, but securing a full-time data scientist role at Google typically requires strong technical skills in machine learning, programming (such as Python or R), and a solid educational background in a related field. Full-time positions often involve a rigorous interview process including technical assessments and behavioral interviews.

Does Google have data science internships?

Yes, Google offers data science internships for students and recent graduates interested in working on real-world projects using tools like Python, R, and SQL. These internships typically last 12 to 14 weeks and provide hands-on experience in data analysis, machine learning, and research within a collaborative 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.

Is a 3.0 GPA good for internships?

For a Google Data Science internship, a 3.0 GPA is generally considered acceptable but may be below the preferred range, as competitive internships often look for GPAs of 3.5 or higher. Strong technical skills, relevant coursework, and project experience can also significantly impact your application. GPA is one factor among others like coding ability, problem-solving skills, and internships or projects 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.

Is 30 too late for data science?

Age is not a strict barrier for a data science internship or career; many professionals transition into data science later in life. Success depends on relevant skills such as programming, statistics, and tools like Python or R, as well as a strong portfolio and continuous learning. Employers value experience and skills over age, making it possible to start or switch to data science at 30 or older.

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 are popular job titles related to Google Internship Data Science jobs in Remote, OR? For Google Internship Data Science jobs in Remote, OR, the most frequently searched job titles are:
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:
Google Internship Data Science jobs near you
Infographic showing various Google Internship Data Science job openings in Remote, OR as of June 2026, with employment types broken down into 20% Internship, 60% Full Time, and 20% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $46,763 per year, or $22.5 per hour.

Senior Data Scientist

SOSi

Myrtle Point, OR

Full-time

Posted 26 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.