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Environmental Data Science Jobs in Silver Spring, MD

Elder Research

Data Scientist

Arlington, VA · On-site

... 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 ...

ECS

Data Scientist

Springfield, VA · On-site

... 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 ...

Elder Research

Data Scientist

Arlington, VA

... 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 ...

Booz Allen Hamilton

Data Scientist

Washington, DC · On-site

... science expertise to create real-world impact. • Work closely with clients to understand their questions and needs and then dig into their data-rich environments to find the pieces of their ...

Inroads

Manager I, Data Science

Washington, DC · On-site +1

$85K/yr

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 ...

Booz Allen Hamilton, Inc.

Data Scientist

Alexandria, VA · On-site

... 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 ...

Booz Allen Hamilton, Inc.

Data Scientist

Alexandria, VA · On-site

... 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 ...

Booz Allen Hamilton

Data Scientist

Alexandria, VA · On-site

... 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 ...

VTG

Data Scientist

Chantilly, VA · On-site

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

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Environmental Data Science information

See Silver Spring, MD salary details

$38.8K

$126.9K

$203.1K

How much do environmental data science jobs pay per year?

As of May 28, 2026, the average yearly pay for environmental data science in Silver Spring, MD is $126,884.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,800.00 and $140,600.00 per year, depending on experience, location, and employer.

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 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 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.

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 are the most commonly searched types of Environmental Data Science jobs in Silver Spring, MD? The most popular types of Environmental Data Science jobs in Silver Spring, MD are:
What are popular job titles related to Environmental Data Science jobs in Silver Spring, MD? For Environmental Data Science jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Environmental Data Science jobs in Silver Spring, MD look for? The top searched job categories for Environmental Data Science jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Environmental Data Science jobs? Cities near Silver Spring, MD with the most Environmental Data Science job openings:
Environmental Data Science jobs near you
Infographic showing various Environmental Data Science job openings in Silver Spring, MD as of May 2026, with employment types broken down into 77% Full Time, 9% Part Time, and 14% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $126,884 per year, or $61 per hour.
Data Scientist

Data Scientist

Elder Research

Arlington, VA • On-site

Full-time

Posted 22 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 Service's 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 science-driven 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.

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