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Environmental Data Science Jobs in Baltimore, MD

Agile Defense

Data Scientist

Fort George G Meade, MD · On-site

$100 - $130/hr

Implement core data science capabilities, such as entity resolution, classification, clustering, or prediction, within containerized environments that adhere to CI/CD, version control, and testing ...

Leidos

Data Scientist

Silver Spring, MD · On-site

$69K - $125K/yr

You will be delivering cutting edge data science capabilities to advance national security ... Experience with an on-prem, air gapped environment and/or Amazon Web Services (AWS/C2S) #NMECDTP ...

Phase2 Technology

Data Scientist

Fort George G Meade, MD · On-site

$77.60 - $176/hr

Ability to work in Windows and Linux OS environments * Bachelor's degree in Operations Research, Applied Mathematics, or Data Science Clearance: Applicants selected will be subject to a security ...

NOVACES

Senior Data Scientist

Baltimore, MD · On-site

$120 - $160/hr

... environments. Certifications: Relevant data science, analytics, cloud, Agile, or project-related certifications helpful. Must be able to obtain a Tier 1 clearance. #J-18808-Ljbffr

NOVACES

Senior Data Scientist

Baltimore, MD · On-site

... environments. Certifications: Relevant data science, analytics, cloud, Agile, or project-related certifications helpful. Must be able to obtain a Tier 1 clearance.

NOVACES

Senior Data Scientist

Baltimore, MD

... environments. Certifications: Relevant data science, analytics, cloud, Agile, or project-related certifications helpful. Must be able to obtain a Tier 1 clearance. Employment Type: FULL_TIME

iNovex Information Systems

Data Scientist 4

Annapolis, MD · On-site

$212K - $267K/yr

You must be able to work in a fast-paced and collaborative environment with competing priorities. The ability to integrate AI techniques is required. The Level 4 Data Scientist shall possess the ...

Parsons

Senior Data Scientist

Aberdeen, MD · On-site

What You'll Be DoingData Science, Analytics & Modeling * Design and implement data science ... or near-real-time environments * Translate mission and system requirements into data-driven ...

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Showing results 21-40

All JobsEnvironmental Data Science JobsEnvironmental Data Science Jobs in Baltimore, MD

Environmental Data Science information

See Baltimore, MD salary details

$37.3K

$122K

$195.3K

How much do environmental data science jobs pay per year?

As of Aug 12, 2026, the average yearly pay for environmental data science in Baltimore, MD is $121,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $135,100.00 per year, depending on experience, location, and employer.

Is environmental data science a good major?

Environmental data science is a strong major for those interested in analyzing environmental data, using tools like GIS and statistical software. It prepares students for roles in environmental monitoring, research, and policy, often requiring skills in programming, data analysis, and environmental science. Job prospects are growing as organizations seek data-driven solutions to environmental challenges.

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 with large datasets and models to inform environmental policies and practices.

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 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 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 Baltimore, MD? The most popular types of Environmental Data Science jobs in Baltimore, MD are:
What are popular job titles related to Environmental Data Science jobs in Baltimore, MD? For Environmental Data Science jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Environmental Data Science jobs in Baltimore, MD look for? The top searched job categories for Environmental Data Science jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Environmental Data Science jobs? Cities near Baltimore, MD with the most Environmental Data Science job openings:
Environmental Data Science jobs near you
Infographic showing various Environmental Data Science job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $121,958 per year, or $58.6 per hour.

Data Scientist

Sand Tech Holdings Limited

Baltimore, MD • On-site

Full-time

Re-posted 3 days ago

Job description

About Sand

Sand Technologies is a global Physical AI company using data and AI to make critical industries work better. We partner with governments, cities and enterprises to improve how essential systems operate across healthcare, water, energy, telecommunications and infrastructure.

Our work delivers proven real-world impact. We have built AI systems that help manage London's water supply, supported telecom network planning across hundreds of cities, and developed digital healthcare platforms serving tens of millions of people across Africa. From intelligent command centers to AI-powered infrastructure platforms, we help organizations sense, analyze and act in complex environments.

Our people are ambitious, curious and relentlessly practical. Our teams work alongside clients in the field, solving hard problems and deploying solutions that last. With colleagues across Africa, Europe, the UK and the US, we operate across the full stack - from research and engineering to deployment and capability building.

Our mission is simple: to harness AI to solve humanity's most pressing challenges.

About the role

We are seeking an experienced Data Scientist to join our growing data science team. As a key contributor, the Data Scientist will be responsible for using their advanced data analysis and machine learning skills to solve complex business problems and drive data-driven decision-making within our organisation and those of our clients. The ideal candidate will have a strong background in statistics, machine learning and data analysis, along with a proven track record of delivering impactful, scalable solutions - with demonstrated experience getting data science solutions into production. Key responsibilities are:

  • Conduct independent (and collaborative) research and development of data science and machine learning models; develop cutting-edge data science and machine learning models that drive business value, leveraging internal and external data sources.
  • You are skilled in, and continue to improve upon your knowledge of decision science, communicating data, domain modelling, predictive modelling, advanced analytics, MLOps, Research and AI Ethics with the willingness to up skill others in these competencies.
  • Collaborate with cross-functional teams: work closely with cross-functional teams to apply data science and machine learning models to business problems, ensuring that models are integrated into scalable products and services.
  • Communicate results and impact: communicate results and impact to stakeholders, including technical and non-technical audiences.
  • Perform cutting edge research in Physical AI, at the intersection of engineering models and AI.
  • Mentor junior data scientists: mentor junior data scientists, fostering a culture of continuous improvement and innovation.
Requirements - Essential
  • 3+ years of applied data science experience in water, wastewater, utilities, or smart infrastructure environments.
  • Demonstrated experience working with operational telemetry data (SCADA, AMI, IoT, sensor systems).
  • Strong expertise in time-series modeling, anomaly detection, and forecasting for infrastructure systems.
  • Experience applying geospatial analytics and/or graph/network modeling in real-world systems.
  • Proven track record of deploying ML solutions into production, including data pipelines, MLOps, and model monitoring.
  • Ability to translate advanced analytics into actionable insights for engineering and operations teams.
  • Strong communication skills and experience working with public-sector or regulated environments.
  • M.Sc. (Master's degree) in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field required; PhD preferred.
Location

This role is not a remote position. We would require our Data Scientist to be able to travel to client sites in Baltimore 3-4 days a week minimum.

Personal Attributes
  • Client Centricity & Integrity: We let Our Clients Run the Company, Surf Like Yvon Chouinard to stay true to our values, and Play the Long Game with integrity.
  • Collaboration and Inclusion: We live by Each One, Teach Ten and ensure Everybody is Welcome.
  • Operational Excellence and Simplicity: We K.I.S.S. by keeping things simple while always striving to Raise the Bar.
  • Action, Ownership, and Execution: We Decide, Get Stuff Done, and Do Hard Things with accountability.
  • Growth, Innovation, and Resilience: We Choose Growth, Pioneer boldly, and remember There is No Failure.

Due to the considerable amount of virtual work and interaction with colleagues and customers in different physical locations internationally, it is essential that the successful applicant has the drive and ethics to succeed in working in small teams physically but in larger efforts virtually. Self-drive to communicate constantly using web collaboration and video conferencing is essential.

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