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Ecology Data Science Jobs (NOW HIRING)

LSU AgCenter

... ecology, statistical modeling, computational biology, genomics, structural biology, experimental ... A Ph.D. in plant pathology, plant biology, data science, computational biology, bioinformatics ...

Louisiana State University

... ecology, statistical modeling, computational biology, genomics, structural biology, experimental ... A Ph.D. in plant pathology, plant biology, data science, computational biology, bioinformatics ...

EHS Support LLC

Scientist

Analyzing environmental data in support of investigation objectives and defined data quality ... Master's in biology, chemistry, geochemistry, ecology, environmental science, or a related field.

Louisiana Workforce Commission

... ecology, statistical modeling, computational biology, genomics, structural biology, experimental ... A Ph.D. in plant pathology, plant biology, data science, computational biology, bioinformatics ...

The Pennsylvania State University

D. degree with expertise in at least two of the following areas: human-environment geography, landscape ecology, land system science, remote sensing/GIS science, data science, or related field.

CSS, Inc

Data Scientist

Charleston, SC · On-site

Experience Required: * Experience with data engineering, data management, or scientific data ... Experience with ecological /environmental datasets and marine monitoring programs. * Familiarity ...

CSS, Inc

Data Scientist

Charleston, SC · On-site

Experience Required: * Experience with data engineering, data management, or scientific data ... Experience with ecological /environmental datasets and marine monitoring programs. * Familiarity ...

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Ecology Data Science information

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$37.5K

$122.7K

$196.5K

How much do ecology data science jobs pay per year?

As of Jun 22, 2026, the average yearly pay for ecology 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 a typical day look like for someone working in Ecology Data Science?

A typical day for an Ecology Data Scientist often involves collecting and cleaning large datasets from field observations or environmental sensors, analyzing complex ecological trends using statistical models, and visualizing findings to inform conservation or policy decisions. You may also collaborate closely with ecologists, field technicians, and GIS specialists to ensure data accuracy and interpretation. Many roles offer a mix of independent analysis and team meetings to discuss project objectives or present research outcomes. This dynamic environment requires adaptability and strong communication skills to contribute effectively to interdisciplinary initiatives.

What are the key skills and qualifications needed to thrive in the Ecology Data Science position, and why are they important?

To excel in Ecology Data Science, you should possess a strong background in ecology or environmental science, coupled with expertise in statistics, programming (e.g., R or Python), and data analysis. Familiarity with GIS software, remote sensing tools, and database management systems is routinely required, and certifications in data science or ecological analysis can be advantageous. Outstanding problem-solving, communication, and teamwork skills help professionals interpret results and collaborate with multidisciplinary stakeholders. These combined competencies are crucial for generating actionable insights from ecological data and guiding environmental decision-making.

What is an Ecology Data Science job?

An Ecology Data Science job involves using data analysis, statistical modeling, and programming to study environmental and ecological systems. Professionals in this field collect, process, and interpret large datasets related to biodiversity, climate change, conservation, and ecosystem health. They often work with GIS mapping, machine learning, and predictive models to support ecological research and decision-making. These roles are found in academia, government agencies, non-profits, and private organizations focused on environmental sustainability.

More about Ecology Data Science jobs
What cities are hiring for Ecology Data Science jobs? Cities with the most Ecology Data Science job openings:
What states have the most Ecology Data Science jobs? States with the most job openings for Ecology Data Science jobs include:
What job categories do people searching Ecology Data Science jobs look for? The top searched job categories for Ecology Data Science jobs are:
Ecology Data Science jobs near you
Infographic showing various Ecology Data Science job openings in the United States as of June 2026, with employment types broken down into 88% Full Time, 6% Part Time, and 6% Temporary. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Postdoctoral Research Fellow in Sustainability and Data Science

Postdoctoral Research Fellow in Sustainability and Data Science

University of Notre Dame

Notre Dame, IN • On-site

Full-time

Posted 10 hours ago

University Of Notre Dame rating

7.5

Company rating: 7.5 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

263rd of 539 rated colleges and universities

Job description

Description
The University of Notre Dame invites applications for a cohort of outstanding Postdoctoral Research Fellows with deep expertise in quantitative data analysis, data science, and artificial intelligence (AI). These fellows will join a dynamic, interdisciplinary team working at the intersection of data innovation and sustainability science, aligned with the values and principles of integral ecology.
The research fellows will contribute to a new research project that is creating a Pan-Amazon Evidence and Action Hub for socio-economic and ecological flourishing in Amazonia. The hub will systematically synthesize and harmonize remote sensing, survey, census, and citizen science data to support analyses of issues for action in partnership with local communities and Indigenous Peoples in the Amazon region. Fellows will integrate and harmonize fragmented data from diverse sources into a coherent, usable form to support novel analyses that advance key sustainability goals. The work of the Hub will generate findings to support the design and adoption of interventions that respond to changing needs of the region and its people around climate change, energy, mining, soil and water contamination, food production and livelihoods.
The postdoctoral cohort will function as a central research skills hub, supporting and elevating the sustainability-related research efforts of faculty and students across Notre Dame. The fellows will help advance impactful, solution-oriented sustainability research that engages ecological, social, economic, and ethical dimensions in an integrated manner.
The postdoctoral fellows will assume the following key responsibilities:
  • Collaborate with faculty to design, implement, and support sustainability-related research projects requiring advanced data analytics.
  • Develop and maintain a centralized platform for the Pan-Amazon Evidence and Action Hub that hosts diverse and harmonized sustainability-related datasets, including environmental, socioeconomic, cultural, and geospatial data.
  • Harmonize, curate, and provide customized datasets across multiple spatial and temporal resolutions tailored to specific research questions and stakeholder needs.
  • Apply advanced statistical, machine learning, and AI techniques to analyze complex datasets and uncover actionable insights.
  • Co-author and support high-impact, interdisciplinary research publications in leading sustainability and environmental science journals.
  • Engage in collaborative grant writing and proposal development to sustain and expand the cohort's research initiatives.

This search is conducted with leadership from Notre Dame's Just Transformations to Sustainability Initiative and Data, AI, and Computing Initiative, both significant investments from the Provost's Office. The Just Transformations to Sustainability Initiative is Notre Dame's University-wide effort to build a sustainable future where people and nature flourish together. The Data, AI, and Computing Initiative's core aim is to advance purposeful data, AI, and computing - excelling in foundational research while catalyzing interdisciplinary collaboration and real-world translation to address pressing societal challenges.
This is a full-time position available with an initial appointment of one-year, renewable for an additional year on the basis of satisfactory performance and availability of funding.
Qualifications
Required Qualifcations:
  • Ph.D. (in hand by the starting date) in Data Science, Computer Science, Statistics, Environmental Science, Sustainability Studies, or a related field with a strong quantitative focus. Applicants with an interdisciplinary degree are welcome.
  • Demonstrated proficiency in data management, data harmonization, and advanced data analysis techniques.
  • Strong programming skills in Python, R, and/or similar software.
  • Experience working with large and complex datasets, including geospatial and temporal data.
  • A strong publication record in data-driven sustainability research or closely related fields.
  • Excellent communication skills and an ability to work collaboratively with researchers from a wide range of disciplines.
  • Spanish language fluency or professional proficiency

Preferred Qualifications:
  • Experience working with socioeconomic data or other indicators of human wellbeing.
  • Experience working in multidisciplinary teams with researchers from diverse backgrounds.

Application Instructions
Applications will be reviewed on a rolling basis starting on November 1, 2025 and will continue until the positions are filled.
Interested applicants should submit the following materials at their earliest convenience.
  1. A cover letter that describes in detail how their research background and qualifications correspond to the position description outlined above.
  2. A detailed CV, including a list of conference presentations, publications, and research collaborations.
  3. A recent publication or dissertation chapter.
  4. Contact information for at least three references.

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