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Google 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 ...

Build / manage production-ready data science product lifecycles, continuous delivery and automation ... Learning, Google Data Engineering, Azure AI Engineer Associate, etc.) * Experience building AI ...

Data Science Lead

Hampton, VA · On-site

$135K - $216K/yr

Familiarity with cloud computing platforms such as AWS , Azure , or Google Cloud . * Certifications such as Certified Data Scientist (CDS) , AWS Certified Machine Learning Specialty , or equivalent.

Familiarity with cloud computing platforms such as AWS , Azure , or Google Cloud . * Certifications such as Certified Data Scientist (CDS) , AWS Certified Machine Learning Specialty , or equivalent.

Data Science Lead

Hampton, VA · On-site

$135K - $216K/yr

Familiarity with cloud computing platforms such as AWS , Azure , or Google Cloud . * Certifications such as Certified Data Scientist (CDS) , AWS Certified Machine Learning Specialty , or equivalent.

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 ...

Experience and Education Bachelor's degree in a quantitative field such as Computer Science ... Power BI Data Analyst Associate Google Data Analytics Professional Certificate Certified Analytics ...

Experience and Education Bachelor's degree in a quantitative field such as Computer Science ... Power BI Data Analyst Associate • Google Data Analytics Professional Certificate • Certified ...

... data science and analytics, data visualization, and share expertise to improve technical ... Preferred : • (Highly preferred) AWS or Google Cloud Professional or Specialty Certification or ...

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 ...

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 ...

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 ...

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 ...

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 Data Science information

See Virginia salary details

$23.8K

$112.7K

$195K

How much do google data science jobs pay per year?

As of Jul 2, 2026, the average yearly pay for google data science in Virginia is $112,749.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,967.00 and $141,503.00 per year, depending on experience, location, and employer.

Can a Data Scientist work in Google?

Yes, Data Scientists can work at Google, where they analyze large datasets, develop machine learning models, and use tools like Python and TensorFlow. Google typically requires relevant experience, strong analytical skills, and a background in computer science or related fields for data science roles.

How much do data scientists make at Google?

Data scientists at Google typically earn a median salary ranging from $120,000 to $160,000 per year, depending on experience, location, and level. Total compensation often includes bonuses, stock options, and other benefits, reflecting the company's competitive pay structure for technical roles requiring skills in machine learning, programming, and data analysis.

What are the key skills and qualifications needed to thrive in the Google Data Science position, and why are they important?

To thrive as a Google Data Science professional, you need a strong foundation in statistical analysis, machine learning, and data manipulation, often supported by a degree in a quantitative field such as computer science, statistics, or mathematics. Proficiency in programming languages like Python or R, experience with large-scale data processing tools (such as SQL, TensorFlow, or BigQuery), and familiarity with cloud-based platforms are commonly required. Excellent problem-solving, communication, and collaboration skills help set candidates apart in effectively translating complex data insights to varied stakeholders. These capabilities are crucial for driving impactful, data-driven decisions within cross-functional teams at Google.

How much does Google pay a Data Scientist?

Google Data Scientists typically earn a base salary ranging from $120,000 to $180,000 annually, with total compensation often including bonuses and stock options that can increase overall earnings. Compensation varies based on experience, location, and skill level, with advanced skills in machine learning and data analysis highly valued.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, and many professionals successfully transition into the field at age 40 or later. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, often through online courses or certifications, and building a strong portfolio. Employers value experience and problem-solving ability, making it possible to start a data science career at any age with dedication.

What is a Google Data Science job?

A Google Data Science job involves analyzing large datasets to provide insights and drive data-informed decisions. Data scientists at Google apply statistical modeling, machine learning, and analytical techniques to solve complex problems in products like Search, Ads, YouTube, and Cloud. They work closely with engineers, product managers, and business teams to develop data-driven solutions. Strong coding skills in Python or SQL, experience with big data tools, and a solid foundation in statistics are essential for this role.

What types of projects do Google Data Science professionals typically work on?

Google Data Science professionals engage in a wide variety of impactful projects, such as optimizing algorithms for product recommendations, improving user experiences through data-driven insights, and developing predictive models to inform business strategies. They often work closely with product managers, engineers, and designers to translate complex data findings into actionable solutions. The work environment is highly collaborative and fast-paced, with opportunities to contribute to innovative initiatives across different Google products and services. This dynamic setting allows data scientists to continuously expand their skill sets and take on new challenges, fostering both personal and professional growth.

What are the most commonly searched types of Google Data Science jobs in Virginia? The most popular types of Google Data Science jobs in Virginia are:
What job categories do people searching Google Data Science jobs in Virginia look for? The top searched job categories for Google Data Science jobs in Virginia are:
What cities in Virginia are hiring for Google Data Science jobs? Cities in Virginia with the most Google Data Science job openings:
Data Science

Data Science

Altagrove LLC

Norfolk, VA • On-site

Full-time

Posted 29 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.