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Temporary Google Data Science Jobs (NOW HIRING)

Deloitte

Google Data Engineering Consultant

Arlington, VA · On-site

$131K - $158K/yr

Required : • Bachelor's degree in Computer Science, Data Science, Information Systems ... Preferred : • Google certifications preferred • Experience with Vertex AI, application ...

Apogee Engineering, LLC

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 ...

New

Google

Data Scientist

San Bruno, CA · On-site

Bachelor's degree in Statistics, Applied Mathematics, Data Science, Business Analytics, Economics ... Learn more about benefits at Google . Position reports to the Google San Bruno, CA office & may ...

Altagrove LLC

Data Science

Norfolk, VA · On-site

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 ...

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

As of Jul 11, 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 are temporary Google data science jobs?

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 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.

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.
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Data Scientist, GenAI Strategy and Operations, DeepMind

Google DeepMind

Mountain View, CA • On-site

Full-time

Posted 10 days ago

Job description

Job Summary:
Google DeepMind is a pioneering AI lab focused on advancing AI development to solve complex global challenges. The Data Scientist role involves using analytical excellence to shape business strategies by processing and interpreting large datasets, collaborating with various teams to enhance operational efficiency and decision-making.
Responsibilities:
• Partner closely with cross-functional leadership to define core operational hypotheses and design metric frameworks.
• Develop, deploy, and scale intuitive, self-service analytical dashboards (PLX, Tableau, or Google Data Studio) to enable real-time monitoring of organizational health and KPIs for stakeholders.
• Programmatize workflows, manage resource dependencies, proactively mitigate risks, and collaborate across internal teams to ensure operational rhythm and milestone execution.
• Act as a trusted advisor to senior leadership by synthesizing complex quantitative findings into clear, narrative-driven presentations. Communicate technical and statistical insights effectively to influence strategic decision-making.
• Apply advanced data science methodologies to evaluate organizational design, productivity, and spending patterns, translating data into insights.
Qualifications:
Required:
• Bachelor's degree in Business Analytics, Information Technology, Computer Science, Data Science, a related field, or equivalent practical experience.
• 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
• 5 years of experience in a consulting role developing and executing performance advertising strategies.
Preferred:
• MBA or Master's degree in Statistics, Data Science, or a related field.
• Experience with advanced data visualization, Business Intelligence (BI) tools, and translating complex datasets into executive-level insights.
• Experience with a scripting language (e.g., Python or Apps Script) to automate data analysis.
Company:
Google DeepMind aims to research and build safe artificial intelligence system to solve intelligence and advance science and humanity. It is a sub-organization of Google. Founded in 2010, the company is headquartered in London, GBR, with a team of 501-1000 employees. The company is currently Late Stage.

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