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Environmental Data Science Jobs in Reston, VA (NOW HIRING)

... environments. You will work directly with government clients, program managers, and technical teams ... You will contribute across the full data science lifecycle, from problem formulation and data ...

... environment where deadlines are important to national security. * Must be a US Citizen * Active Top Secret security clearance with SCI + CI Poly eligibility * A Bachelor's Degree in Data Science ...

... science expertise to create real-world impact. You'll work closely with clients to understand their questions and needs in order to then dig into their data-rich environments to find the pieces of ...

... science expertise to create real-world impact. You'll work closely with clients to understand their questions and needs in order to then dig into their data-rich environments to find the pieces of ...

... science expertise to create real-world impact. You'll work closely with clients to understand their questions and needs in order to then dig into their data-rich environments to find the pieces of ...

... science expertise to create real-world impact. You'll work closely with clients to understand their questions and needs in order to then dig into their data-rich environments to find the pieces of ...

As Manager I, Data Science, you will work with a team of analysts, data scientists, and engineers ... Inroads offers a friendly work environment and competitive compensation and benefits package ...

... science expertise to create real-world impact. You'll work closely with clients to understand their questions and needs in order to then dig into their data-rich environments to find the pieces of ...

Deploy and monitor machine learning models in production environments * Continuously improve model performance and accuracy * Stay current with emerging data science techniques, tools, and ...

Data science tasks will include analysis, query, aggregation, visualization, extract/transform/load ... environments to reduce or eliminate manual effort in data processing by automating common processes.

You will leverage data science, machine learning, and statistical techniques to analyze, model, and ... Create and operate in distributed analytic environments, scaling algorithms to handle datasets ...

Data science tasks will include analysis, query, aggregation, visualization, extract/transform/load ... environments to reduce or eliminate manual effort in data processing by automating common processes.

Data Scientist

Herndon, VA · On-site

$51K - $82K/yr

Stellar communication skills, forward thinking, and the ability to work in a fast-paced team environment will be pivotal. This role will serve as a hands-on data science solution developer ...

Data Scientist

Herndon, VA · On-site

$112K - $179K/yr

Professional or graduate certificate in Data Science from a university or major online learning platform, * Experience working in the customer environment is preferred. Security Clearance: This ...

Professional or graduate certificate in Data Science from a university or major online learning platform, * Experience working in the customer environment is preferred. Security Clearance: This ...

Generate representative data sets for systems development and data science initiatives. * Build ... Experience organizing and managing tasks in an agile environment (JIRA/Confluence). * Ability to ...

You will leverage data science, machine learning, and statistical techniques to analyze, model, and ... Create and operate in distributed analytic environments, scaling algorithms to handle datasets ...

Stellar communication skills, forward thinking, and the ability to work in a fast-paced team environment will be pivotal. This role will serve as a hands-on data science solution developer ...

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Environmental Data Science information

See Reston, VA salary details

$39K

$127.7K

$204.4K

How much do environmental data science jobs pay per year?

As of Jun 15, 2026, the average yearly pay for environmental data science in Reston, VA is $127,692.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,500.00 and $141,500.00 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 job categories do people searching Environmental Data Science jobs in Reston, VA look for? The top searched job categories for Environmental Data Science jobs in Reston, VA are:
What cities near Reston, VA are hiring for Environmental Data Science jobs? Cities near Reston, VA with the most Environmental Data Science job openings:
Data Scientist

Other

Posted 9 days ago


Job description

Data Scientist


General Information

Requisition # 674

Locations USA-VA-Arlington

Posting Date 03/04/2026

Security Clearance Required - IRS MBI

Remote Type Hybrid

Time Type Full time


Description & Requirements

Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Data Scientist to join our team in Arlington, VA. This role is a remote role preferably in the Washington DC area.

As a Data Scientist, you will support the Internal Revenue Services mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data environments. You will work directly with government clients, program managers, and technical teams to understand business and compliance challenges, design analytical approaches, and deliver data-driven solutions that inform enforcement, audit prioritization, and fraud prevention efforts.

In this role, you will develop, test, and deploy predictive and statistical models using structured and unstructured data to identify anomalies, non-compliance risk, and potential fraud within tax records and related datasets. You will contribute across the full data science lifecycle, from problem formulation and data exploration through model validation, deployment, and stakeholder communication.

Responsibilities include but are not limited to:

  • Prior programming experience, preferably in Python or R, including data exploration, feature engineering, model development, and writing modular, reusable, well-documented code within an iterative development process that includes peer review and collaboration
  • Demonstrated experience using Python, SQL, and Databricks for data analysis, modeling, statistical evaluation, and working with Markdown for technical documentation
  • Explore, clean, and wrangle large, complex datasets to uncover insights and identify opportunities for data sciencedriven solutions in support of assessments, gap analyses, and actionable recommendations for IRS stakeholders
  • Design, develop, test, validate, and implement quantitative and qualitative data science solutions and predictive risk models (including audit selection, refund review, and fraud prevention initiatives) that are modular, maintainable, adaptable to evolving government and regulatory requirements, and supported by robustness, sensitivity, and significance testing to ensure defensible and explainable results
  • Apply statistical and machine learning techniques (supervised and unsupervised) to anomaly detection, fraud identification, and non-compliance risk scoring to help prioritize cases based on compliance risk, fraud indicators, and business impact
  • Collaborate with clients, subject matter experts, and cross-functional teams to refine problem statements, requirements, and analytical approaches, while demonstrating the ability to work independently in a collaborative, fast-paced environment
  • Prepare and deliver technical and non-technical briefings, reports, and presentations to audiences with varying levels of analytical sophistication, translating business and compliance needs into technical solutions with strong interpersonal, written, and verbal communication skills

Minimum Qualifications:

  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences
  • 2-10+ years of experience in data science, analytics, or a related technical field
  • Experience using version control systems (e.g., Git) and collaborative development practices
  • Strong understanding of relational databases and SQL
  • Comfortable learning new tools, methodologies, and domains, including working outside your comfort zone
  • Strong analytical mindset with a willingness to tackle complex mathematical and statistical challenges
  • Willingness to travel and work on-site at client locations as required by project needs

Preferred Qualifications:

  • Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields; experience applying advanced statistical concepts including sampling considerations, bias detection, weighting techniques, handling missing or outlier data, exploratory analysis, and longitudinal forecasting; and understanding of the data analytics lifecycle (e.g., CRISP-DM)
  • Experience with PySpark, Unity Catalog, and Jobs in Databricks, with familiarity using platforms and tools such as Databricks and AWS
  • Experience with Natural Language Processing (NLP) and text analytics applied to unstructured documents or case notes, as well as graph analytics and network analysis to identify relationships, fraud rings, or interconnected entities
  • Experience with containerization and environment management (e.g., venv, conda)
  • Experience operating in secure or remote government environments, including use of bash and command-line tools

Clearance Requirements:

  • Must currently possess an IRS Public Trust clearance with Full Background Investigation

Physical Requirements:

  • Must be able to remain in a stationary position 50%
  • Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
  • Frequently communicates with co-workers, management, and customers, which may involve delivering presentations. Must be able to exchange accurate information in these situation

About Elder Research, Inc - People Centered. Data Driven

Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.

If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.