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Environmental Data Science Jobs in Virginia (NOW HIRING)

Altagrove LLC

Data Science

Norfolk, VA · On-site

Support cloud-native and hybrid data environments leveraging AWS, Azure, Kubernetes, and modern ... Strong proficiency in Python and experience with modern data science and engineering frameworks.

JCTM, LLC

Data Science SME

Quantico, VA · On-site

$119K - $133K/yr

The effective use of data is central to preparing Marine Corps forces for the future operating environment. What if you could apply your data science expertise to help the Marine Corps Warfighting ...

JCTM, LLC

Data Science SME

Quantico, VA · On-site

$119K - $133K/yr

The effective use of data is central to preparing Marine Corps forces for the future operating environment. What if you could apply your data science expertise to help the Marine Corps Warfighting ...

Fanniemae

Data Science Advisor

Reston, VA · On-site

Experience in Internal Audit, Risk Management, Model Risk Management, or other highly regulated environments. * Experience applying advanced data science methods such as regression, SVM (support ...

VTG

Data Scientist

Chantilly, VA

Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, or related field ... delivery environments Data Scientist III * Bachelor's degree in Data Science, Statistics ...

VTG

Data Scientist

Chantilly, VA · On-site

Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, or related field ... environments

Booz Allen Hamilton

Data Science Engineer

Mclean, VA · On-site

$116K - $139K/yr

As a Data Science Engineer, you will develop workflows and platforms to transform complex data sets ... environment. • Use your passion to master new tools and techniques and identify needed system ...

Booz Allen Hamilton, Inc.

Data Science Engineer

Mclean, VA · On-site

$77K - $176K/yr

Here, you'll work with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced and agile environment. As a Data Science Engineer at Booz ...

Carmax

Senior Manager, Data Science

Richmond, VA

Apply advanced data science techniques across the full model lifecycle: * Design, training ... Manage and prioritize multiple projects in a fast-paced environment * Foster both technical and ...

Booz Allen Hamilton, Inc.

Data Science Engineer

Mclean, VA · On-site

$77K - $176K/yr

Here, you'll work with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced and agile environment. As a Data Science Engineer at Booz ...

Booz Allen Hamilton

Data Science Engineer

Mclean, VA

$77K - $176K/yr

Here, you'll work with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced and agile environment. As a Data Science Engineer at Booz ...

Carmax

Senior Manager, Data Science

Richmond, VA · On-site

Apply advanced data science techniques across the full model lifecycle: * Design, training ... Manage and prioritize multiple projects in a fast-paced environment * Foster both technical and ...

Booz Allen Hamilton

Data Science Engineer

Mclean, VA

$77K - $176K/yr

Here, you'll work with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced and agile environment. As a Data Science Engineer at Booz ...

AArete

Data Science Analyst

Vienna, VA

Description Data Science Analyst AArete is one-of-a-kind when it comes to consulting firm culture ... Demonstrated ability to learn and adapt quickly in fast-changing AI environments, with passion for ...

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Showing results 1-20

All JobsEnvironmental Data Science JobsEnvironmental Data Science Jobs in Virginia

Environmental Data Science information

See Virginia salary details

$37.2K

$121.7K

$194.8K

How much do environmental data science jobs pay per year?

As of Jun 15, 2026, the average yearly pay for environmental data science in Virginia is $121,686.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,700.00 and $134,800.00 per year, depending on experience, location, and employer.

What does an environmental data scientist do?

An environmental data scientist analyzes environmental data to identify patterns, assess environmental risks, and support decision-making. They use statistical tools, programming languages like Python or R, and GIS software to interpret data related to climate, pollution, and natural resources, often working in research or consulting settings.

Can data scientists make $300k?

Environmental data scientists can potentially earn $300,000 or more at senior levels or in specialized roles, especially with extensive experience, advanced skills in machine learning, and working in high-demand industries or organizations. However, such salaries are typically achieved through seniority, leadership positions, or in regions with higher compensation standards.

What is Environmental Data Science?

Environmental Data Science is an interdisciplinary field that uses statistical, computational, and analytical techniques to collect, analyze, and interpret large sets of data related to the environment. Professionals in this field work on issues like climate change, pollution, biodiversity, and natural resource management by extracting meaningful insights from complex environmental datasets. Their work supports decision-making for policy, conservation, and sustainability initiatives. Environmental data scientists often collaborate with ecologists, geographers, and policymakers to address environmental challenges using data-driven approaches.

Is 40 too late for data science?

Environmental Data Science is a field that values skills and experience over age, and many professionals transition into it later in their careers. Gaining relevant knowledge in programming, statistics, and environmental science can be achieved at any age, and employers often prioritize expertise and problem-solving ability over age-related factors.

What are some common challenges faced by environmental data scientists when working with real-world datasets?

Environmental data scientists often encounter challenges such as incomplete or inconsistent data, varying data formats, and the need to integrate information from multiple sources like sensors, satellites, and field observations. Addressing missing values, data quality issues, and ensuring proper geospatial alignment can be time-consuming but is essential for producing reliable analyses. Collaboration with domain experts and stakeholders is frequently required to interpret findings and ensure that the results are actionable for environmental policy or management decisions.

What is the difference between Environmental Data Science vs Environmental Data Analyst?

AspectEnvironmental Data ScienceEnvironmental Data Analyst
Required CredentialsTypically requires a degree in data science, environmental science, or related fields; often includes programming and statistical certificationsUsually requires a degree in environmental science, geography, or related fields; may include basic data analysis certifications
Work EnvironmentResearch labs, data centers, environmental agencies, or consulting firmsEnvironmental agencies, research organizations, or consulting firms
Employer & Industry UsageUsed in environmental research, climate modeling, and policy analysisUsed in environmental monitoring, reporting, and data interpretation

Environmental Data Science focuses on developing models and algorithms to analyze complex environmental data, often requiring advanced programming skills. In contrast, Environmental Data Analysts primarily interpret and visualize environmental data to support decision-making. Both roles are vital but differ in technical depth and scope.

What is the highest paying environmental science job?

Environmental Data Science roles such as senior environmental data scientists or environmental analytics managers tend to have the highest salaries in the field, often exceeding $100,000 annually. These positions typically require advanced skills in data analysis, programming, and environmental modeling, and may involve leadership responsibilities or specialized expertise in areas like climate modeling or sustainability analytics.

What are the key skills and qualifications needed to thrive as an Environmental Data Scientist, and why are they important?

To thrive as an Environmental Data Scientist, you need strong quantitative skills, expertise in environmental science, and a relevant degree in data science, statistics, or a related field. Familiarity with data analysis tools such as Python, R, GIS software, and experience with large datasets or machine learning techniques is typical. Exceptional problem-solving abilities, communication skills, and attention to detail set top performers apart in this field. These competencies are crucial for effectively interpreting complex environmental data, informing policy, and driving impactful sustainability initiatives.
What are the most commonly searched types of Environmental Data Science jobs in Virginia? The most popular types of Environmental Data Science jobs in Virginia are:
What are popular job titles related to Environmental Data Science jobs in Virginia? For Environmental Data Science jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Environmental Data Science jobs in Virginia look for? The top searched job categories for Environmental Data Science jobs in Virginia are:
What cities in Virginia are hiring for Environmental Data Science jobs? Cities in Virginia with the most Environmental Data Science job openings:
Environmental Data Science jobs near you
Infographic showing various Environmental Data Science job openings in Virginia as of June 2026, with employment types broken down into 84% Full Time, 8% Part Time, and 8% Contract. Highlights an 100% In-person job distribution, with an average salary of $121,686 per year, or $58.5 per hour.
Data Science

Data Science

Altagrove LLC

Norfolk, VA • On-site

Full-time

Posted 12 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.