1

Environmental Data Science Jobs (NOW HIRING)

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 ...

Manage the data science projects in an Agile environment, provide coaching and mentorship to team members as needed * Establish Data Science role models and best practices in the organization

next page

Showing results 1-20

Environmental Data Science information

See salary details

$37.5K

$122.7K

$196.5K

How much do environmental data science jobs pay per year?

As of Jun 30, 2026, the average yearly pay for environmental data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 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.
More about Environmental Data Science jobs
What cities are hiring for Environmental Data Science jobs? Cities with the most Environmental Data Science job openings:
What are the most commonly searched types of Environmental Data Science jobs? The most popular types of Environmental Data Science jobs are:
What states have the most Environmental Data Science jobs? States with the most job openings for Environmental Data Science jobs include:

Director, Data Science: Data Science Tools

Liberty Information Technology Limited

Portsmouth, NH • On-site, Remote

Full-time

Posted 16 days ago


Job description

Description

The Data Science Infrastructure organization within USRM is hiring a Senior Technical Professional, Data Scientist to join the Data Science Tools team. This role will focus on improving the end-to-end modeling workflow for USRM Data Science by building internal tools, pipelines, and applications that streamline model development, evaluation, deployment, and iteration. The ideal candidate is highly technical, proactive, and motivated by building systems that help other data scientists work more efficiently.

**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel. **

Responsibilities:

  • Design and build internal tools, pipelines, and applications that improve model development, evaluation, and deployment
  • Own strategy and roadmaps for improving data science workflows and tooling across USRM
  • Design, build, and maintain Python packages used across the organization
  • Evaluate and implement AI agent capabilities in tooling using approaches such as MCP, RAG, PydanticAI, LangChain, or related frameworks
  • Work with workflow and modeling tools such as Luigi, Airflow, Celery, MLflow, H2O, scikit-learn, Optuna, and LightGBM, as well as Python development tools such as Pydantic, FastAPI, uv, ruff, and pytest
  • Promote MLOps and AI agent best practices in collaboration with groups such as Enterprise Data & Data Science
  • Stay current on developments in open-source data science frameworks, MLOps, and agentic coding practices
  • Help shape the direction of the Tools team and contribute to a culture of ownership, collaboration, and continuous improvement

The ideal candidate will have:

  • Professional experience building and maintaining Python-based data science or Machine Learning tooling used by multiple end users or teams
  • Worked with any of the following in a professional setting: Git, Bash/shell scripting, uv, pre-commit, ruff, pytest, or Pydantic
  • Built, deployed, or maintained workflows or pipelines using any of the following: Airflow, Luigi, Celery, Databricks, or MLflow
  • Implemented or supported AI/LLM-based tooling using frameworks such as PydanticAI, LangChain, MCP, or RAG
  • Developed, reviewed, or maintained internal Python packages, APIs, or data science applications using tools such as FastAPI, Streamlit, Dash, NiceGUI, or Plotly
  • Applied agentic AI techniques in day-to-day development and incorporate AI capabilities directly into tools and applications where they create meaningful value for data scientists
Qualifications
  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Ability to establish and build relationships within and outside the organization.
  • Ability to give effective training and presentations to management and other groups.
  • Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
  • Broad knowledge of business drivers and market context.
  • Has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of  8 years of relevant experience.

Employees may apply for a new role after completing 12 months of employment in their current position.

Employees should review all role requirements and apply only for positions for which they are eligible. Hiring processes may vary by country, including differences in procedures, requirements, and timelines.  For country-specific details, please consult your local recruiting / HR team.

About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/BenefitsLiberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.Fair Chance Notices

  • California
  • Los Angeles Incorporated
  • Los Angeles Unincorporated
  • Philadelphia
  • San Francisco
Employment Type: FULL_TIME