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Conservation Data Science Jobs (NOW HIRING)

neptune technologies

Data Scientist

Duluth, GA · On-site

... conservation and utility operational improvements. Responsibilities • Collaborate with team members to develop and deploy machine learning models and data science solutions. • Work with Product ...

neptune technologies

Senior Data Scientist

Duluth, GA · On-site

... data science solutions, mentor junior data scientists, and drive Neptune's AI transformation initiatives. This role provides direct impact on utility operations, water conservation efforts, and ...

Neptune

Senior Data Scientist

Duluth, GA · On-site

... data science solutions, mentor junior data scientists, and drive Neptune's AI transformation initiatives. This role provides direct impact on utility operations, water conservation efforts, and ...

SOLTECH

Data Scientist

Duluth, GA

... conservation and operational efficiency initiatives. This is an exciting opportunity to grow your ... Key Responsibilities Design, develop, and deploy machine learning models and scalable data science ...

Arkansas Jobs

CONSERVATION SPECIALIST

Little Rock, AR · On-site

$17.38/hr

Collect environmental data related to air quality, water quality, soil health, and other natural ... Bachelor's degree in environmental science, conservation biology, natural resources management, or ...

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$37.5K

$122.7K

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How much do conservation data science jobs pay per year?

As of Jun 3, 2026, the average yearly pay for conservation 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 is a Conservation Data Science job?

A Conservation Data Science job involves using data analysis, machine learning, and geographic information systems (GIS) to support environmental and wildlife conservation efforts. Professionals in this field collect, clean, and analyze ecological data to identify trends, model species distributions, and inform conservation policies. They often collaborate with researchers, government agencies, and nonprofits to optimize resource management and biodiversity protection. This role requires proficiency in programming, statistics, and domain-specific knowledge of conservation science.

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

To thrive in Conservation Data Science, a strong foundation in data analysis, statistics, ecology or environmental science, and a relevant academic background such as a bachelor's or master's degree is essential. Familiarity with tools such as R, Python, GIS software, and experience working with large ecological datasets or conservation platforms is often required. Excellent problem-solving, attention to detail, and communication skills enable collaboration with multidisciplinary teams and effective translation of data insights to non-technical stakeholders. These capabilities are crucial for transforming complex environmental data into actionable conservation strategies and measurable impact.

What types of projects or datasets do Conservation Data Scientists typically work with?

Conservation Data Scientists often engage with projects analyzing biodiversity trends, wildlife populations, land use changes, or climate impact assessments by working with geospatial, remote sensing, and field survey datasets. This role may involve building predictive models for species distribution, conducting statistical analyses to guide conservation policy, or creating data visualizations for stakeholder reports. You’ll commonly collaborate with ecologists, GIS specialists, field researchers, and policy teams to ensure data-driven decision-making. Working in this field provides exposure to practical conservation challenges and offers opportunities to contribute directly to environmental preservation initiatives.
More about Conservation Data Science jobs
What cities are hiring for Conservation Data Science jobs? Cities with the most Conservation Data Science job openings:
What are the most commonly searched types of Conservation Data Science jobs? The most popular types of Conservation Data Science jobs are:
What states have the most Conservation Data Science jobs? States with the most job openings for Conservation Data Science jobs include:
What job categories do people searching Conservation Data Science jobs look for? The top searched job categories for Conservation Data Science jobs are:
Conservation Data Science jobs near you
Infographic showing various Conservation Data Science job openings in the United States as of May 2026, with employment types broken down into 6% As Needed, 6% Full Time, 82% Part Time, and 6% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist

Data Scientist

neptune technologies

Duluth, GA • On-site

Full-time

Posted 15 days ago

Job description

Position Summary

As a Data Scientist, you will be responsible for developing and implementing machine learning models and analytical solutions that support our water utility intelligence platform. This position involves analyzing large-scale IoT data from water meters, building predictive models, and collaborating with cross-functional teams to deploy data science solutions into production. You will work closely with senior data scientists, software engineers, and Product Management to translate business requirements into actionable insights and ML capabilities. This role offers the opportunity to grow your skills in production ML, cloud technologies, and contribute directly to water conservation and utility operational improvements.

Responsibilities
• Collaborate with team members to develop and deploy machine learning models and data science solutions.
• Work with Product Management to understand requirements and translate them into analytical approaches.
• Build machine learning models for water consumption forecasting, anomaly detection, leak detection, and predictive maintenance.
• Analyze large-scale time-series data from IoT devices and water utility operations.
• Develop data processing workflows using Python, SQL, and distributed computing frameworks.
• Conduct exploratory data analysis to identify patterns, trends, and insights in utility data.
• Perform feature engineering and model experimentation to improve predictive performance.
• Create data visualizations and reports to communicate findings to stakeholders.
• Implement data quality checks and validation procedures for analytical pipelines.
• Collaborate with software engineers to integrate ML models into Neptune 360 platform.
• Monitor model performance and contribute to maintenance of production ML systems.
• Document analytical methodologies, code, and model implementations.
• Participate in code reviews and follow data science best practices.
• Work with cloud-based data infrastructure and ML tools (AWS preferred).
• Stay current with developments in machine learning and data science techniques.
• Participate in sprint planning and demonstrate completed work at the end of every iteration.
• Support senior data scientists with complex analytical projects.
• Continuously develop technical skills through self-directed learning and training.

Experience

• 3+ years of experience in data science, machine learning, or related analytical roles.
• 3+ years of experience with Python and data science libraries (pandas, NumPy, scikit-learn).
• Strong experience with SQL and relational databases.
• Experience building and evaluating machine learning models.
• Understanding of statistical analysis and experimental design principles.
• Experience with data visualization tools and techniques.
• Familiarity with cloud platforms (AWS, Azure, or GCP).
• Experience with version control systems (Git).
• Understanding of software development best practices.
• Ability to work in Agile/iterative development environments.
• Strong problem-solving skills and attention to detail.
• Ability to communicate technical concepts clearly to both technical and non-technical
audiences.
• Demonstrated ability to learn new technologies and tools quickly.
• Continued professional development through courses, certifications, or projects.
• Preferred: Experience with PySpark or distributed computing frameworks.
• Preferred: Experience with time-series analysis and forecasting.
• Preferred: Experience with AWS services (SageMaker, Lambda, S3, Redshift).
• Preferred: Experience with deep learning frameworks (TensorFlow, PyTorch).
• Preferred: Experience deploying models to production environments.
• Preferred: Experience with IoT data or utility operations.

Education
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or
related quantitative field, or combination of education and equivalent experience.

Location: Duluth, GA

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