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Temporary Google Data Science Jobs (NOW HIRING)

Data Scientist

Colorado Springs, CO · On-site

$155K - $190K/yr

Google Data Analytics Professional Certificate; IBM Data Science Professional Certification. Qualifications Minimum Experience: Citizenship: Must be a US citizen Clearance: Must have and be able to ...

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 ...

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Temporary Google Data Science information

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$37.5K

$122.7K

$196.5K

How much do temporary google data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for temporary google data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a temporary Google data scientist?

Temporary Google data science jobs are short-term positions at Google where professionals work on data-driven projects, such as analyzing large datasets, building predictive models, and providing actionable insights. These roles often last from a few months up to a year and can be part of contract work, internships, or project-based assignments. Temporary data scientists at Google collaborate with teams across the company to solve complex problems, improve products, and support decision-making. These positions usually require strong analytical skills, experience with programming languages like Python or R, and familiarity with machine learning techniques.

What are some typical challenges faced by data scientists in temporary roles at Google?

Temporary data scientists at Google often face the challenge of quickly onboarding to new projects and adapting to the company's fast-paced environment. Since assignments are time-bound, there’s a need to rapidly understand existing data infrastructure, collaborate with diverse teams, and deliver actionable insights within tight deadlines. Additionally, building rapport with permanent staff and accessing proprietary data or tools can require extra initiative. However, these challenges provide valuable exposure to Google’s cutting-edge practices and can significantly enhance your professional network and skill set.

What are the key skills and qualifications needed to thrive as a temporary Google data scientist, and why are they important?

To thrive as a Temporary Google Data Scientist, you need strong analytical skills, expertise in statistics, and a solid foundation in programming languages such as Python or R, typically supported by a degree in a quantitative field. Familiarity with machine learning frameworks, big data tools like SQL and TensorFlow, and experience with data visualization platforms such as Tableau are highly valuable. Strong problem-solving abilities, adaptability, and effective communication skills are crucial for collaborating on fast-paced projects and presenting findings to diverse stakeholders. These competencies enable data-driven decision-making and ensure impactful contributions within a dynamic, innovative environment.
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Cities with the most Temporary Google Data Science job openings:

What are the most commonly searched types of Google Data Science jobs?

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What states have the most Temporary Google Data Science jobs?

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Infographic showing various Temporary Google Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Full-time

Re-posted 14 days ago


Job description

Overview

Apogee is seeking a Data Scientist (DS) to support the U.S. Army Space and Missile Defense Command (USASMDC). This role applies data science, statistics, and automation to mission analytics, helping operational and intelligence teams process large, complex datasets and convert them into actionable insights in support of space and missile defense priorities.

The Data Scientist partners with analysts and technical stakeholders to identify high-value analytic problems, engineer and curate datasets, and develop reproducible pipelines and models to automate workflows and enrich mission data. Responsibilities include data exploration and feature engineering; building and evaluating statistical/ML approaches (as appropriate); developing scripts, tools, and dashboards to support analysis and reporting; and communicating results through clear documentation and briefings. The DS also supports data governance and quality efforts, ensures methods are transparent and repeatable, and transitions solutions into operational use in coordination with Government leads and mission users.

 

This is a full-time opportunity at Petterson Space Force Base (PSFB), CO.

****Contingent Upon Contract Award****

Responsibilities
  • Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big-data environment.
  • Demonstrate expert knowledge of Python, and Jupyter Notebooks and/or Jupyter Labs.
  • Author cogent and logical scripts using Python and other applicable languages in a virtual environment using common Integrated Development Environments (IDE) such as VS Code, Spyder, PyScript, or Jupyter Notebooks.
  • Develop and use advanced software programs, algorithms, query techniques, models to solve complex intelligence problems, and automated processes to normalize, integrate, and evaluate data.
  • Debug existing and future Python code; refactor legacy code to ensure continued security, functionality, and compatibility.
  • Document and block-comment all code to ensure recoverability and error-checking, and enhance reading, checking, and maintaining code in accordance with common data science and coding standards, such as PEP-8 for Python,5 or using style-guide features embedded in common IDE applications, such as Spyder, VS Code, PyScript or others upon approval by the Government.
  • Collaborate across multi-discipline teams to ensure connectivity between various data sources and business problems.
  • Identify meaningful insights, interpret, and communicate findings, plus make recommendations to stakeholders.
  • Analyze requirements and evaluate technologies for data science capabilities including Natural Language Processing, Machine Learning, predictive modeling, statistical analysis, and hypothesis testing.
  • Maintain awareness of emerging analytics and big-data technologies.
  • Complete required course NSA NETA1400 (Technology Fundamentals for Analysis); recommended completion of any of the following NSA Courses: NETA2402/NETA2108 (Analysis II), RPTG2238, RPTG2235, RPTG3225, RPTG3222 (Basic Analytical Reporting) or equivalent curriculum.
  • Complete recommended certifications: Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE), Associate Big Data Analyst (ABDA), and Senior Data Scientist (SDS); Google Data Analytics Professional Certificate; IBM Data Science Professional Certification.
Qualifications

Minimum Experience:

Citizenship: Must be a US citizen Clearance: Must have and be able to maintain a Top Secret (TS) with Sensitive Compartmented Information (SCI) adjudicationEducation: Bachelors DegreeYears of Experience: 7+ years experience in data science/analytics engineering/software development in big-data environments.

Additional Experience:

  • Expert Python skills; heavy use of Jupyter Notebooks/Labs and common IDEs (e.g., VS Code/Spyder).
  • Proven ability to build and sustain automated data workflows (ingest/normalize/integrate/enrich/evaluate) using algorithms, queries, and models.
  • Strong SDLC skills: debugging, refactoring legacy code, and maintaining secure/compatible codebases.
  • Code quality discipline: clear documentation/block comments and adherence to PEP-8 (or equivalent style enforcement).
  • Working knowledge of data architecture and ability to collaborate across multi-discipline teams to connect data sources to mission problems.
  • Ability to communicate findings and recommendations to stakeholders.
  • Experience applying/evaluating ML/NLP, predictive modeling, and statistical methods (hypothesis testing).
  • NSA NETA1400 (Technology Fundamentals for Analysis) completion, or Government-approved equivalent.

Preferred Qualifications:Additional Experience:

  • NSA courses: NETA2402/NETA2108 and/or RPTG2238/2235/3225/3222 (or equivalent).
  • Certifications: DASCA (ABDE/ABDA/SDS), Google Data Analytics, and/or IBM Data Science.
  • Experience transitioning prototypes into reusable, analyst-ready tools/pipelines and tracking emerging big-data/analytics tech.

Additional InformationLocation: Petterson Space Force Base (PSFB), COOn-siteTravel: 10%

Pay RangeUSD $155,000.00 - USD $190,000.00 /Yr.Employment Type: OTHER