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Wildlife Conservation Machine Learning Jobs (NOW HIRING)

Defender of Wildlife

Senior Attorney

Washington, DC · On-site

$160K - $180K/yr

... public lands, and wildlife conservation laws, including related regulations and policies ... C Operating machinery and/or power tools. N Operating motor vehicles or heavy equipment. N ...

Defender of Wildlife

Senior Attorney

Denver, CO · On-site

$160K - $180K/yr

... public lands, and wildlife conservation laws, including related regulations and policies ... C Operating machinery and/or power tools. N Operating motor vehicles or heavy equipment. N ...

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Wildlife Conservation Machine Learning information

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$25K

$64.9K

$127K

How much do wildlife conservation machine learning jobs pay per year?

As of Jun 7, 2026, the average yearly pay for wildlife conservation machine learning in the United States is $64,945.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,500.00 and $74,000.00 per year, depending on experience, location, and employer.

How does a Wildlife Conservation Machine Learning specialist typically collaborate with field researchers and conservation teams?

Wildlife Conservation Machine Learning specialists frequently work in close partnership with field researchers, ecologists, and conservation teams to develop, implement, and refine data-driven solutions. They often translate ecological questions into machine learning problems, analyze large datasets (like camera trap images or acoustic recordings), and communicate findings in accessible ways to inform conservation actions. Regular collaboration ensures that the algorithms and tools developed are practical, ethical, and directly support conservation priorities. This team-based approach not only enhances project outcomes but also helps specialists gain a deeper understanding of ecological contexts and real-world conservation challenges.

What is the difference between Wildlife Conservation Machine Learning vs Wildlife Biologist?

AspectWildlife Conservation Machine LearningWildlife Biologist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of machine learningDegree in Biology, Ecology, or related fields; fieldwork experience
Work EnvironmentResearch labs, data centers, field data analysisFieldwork, wildlife reserves, research stations
Industry UsageTechnology-driven conservation projects, data analysisField research, species monitoring, ecological studies

Wildlife Conservation Machine Learning focuses on developing algorithms to analyze ecological data, while Wildlife Biologists conduct fieldwork to study animals directly. Both roles support conservation but differ in skills and work settings.

What are the key skills and qualifications needed to thrive as a Wildlife Conservation Machine Learning Specialist, and why are they important?

To thrive as a Wildlife Conservation Machine Learning Specialist, you need a solid background in ecology, data analysis, and machine learning, often supported by a degree in computer science, environmental science, or a related field. Proficiency with programming languages like Python or R, experience with machine learning frameworks (e.g., TensorFlow, PyTorch), and knowledge of GIS systems are typically required. Strong problem-solving, collaboration, and communication skills help translate technical findings into conservation strategies and engage with interdisciplinary teams. These skills ensure effective use of advanced analytics to address conservation challenges, inform policy, and drive evidence-based wildlife protection.

What is wildlife conservation machine learning?

Wildlife conservation machine learning refers to the use of artificial intelligence and data-driven algorithms to support wildlife protection efforts. This field involves analyzing large datasets, such as images from camera traps, audio recordings, or satellite data, to monitor animal populations, detect poaching activities, and study animal behavior. By automating and enhancing data analysis, machine learning helps conservationists make more informed decisions, allocate resources more effectively, and ultimately increase the impact of conservation projects.
Infographic showing various Wildlife Conservation Machine Learning job openings in the United States as of May 2026, with employment types broken down into 5% Internship, 50% Full Time, 20% Part Time, and 25% Temporary. Highlights an 100% In-person job distribution, with an average salary of $64,945 per year, or $31.2 per hour.
Zoological Park Attendant, Central Park Zoo

Zoological Park Attendant, Central Park Zoo

New York Aquarium

New York, NY

$15.25 - $19.50/hr

Other

Posted 8 days ago

Job description

Department: Operations and Maintenance
Title: Zoological Park Attendant
Location: Central Park Zoo
Employment Type: Full-Time
Reports to: Director of City Zoos Operations and Maintenance, Facility Director, O&M Manager and Assistant Manager, Facility O&M Supervisor
About Wildlife Conservation Society (WCS)
WCS stands for wildlife and wild places. As the world's premier wildlife conservation organization, WCS has a long track record of achieving innovative, impactful results at scale. We run field programs spanning 60 countries and the entire ocean.  We build on a unique foundation: Our reach is global; we discover through best-in-class science; we protect through work on the ground with local and indigenous people; we inspire through our world-class zoos, aquarium, and education programs; and we leverage our resources through partnerships and powerful policy influence.  Our more than 4,000 diverse, passionately committed team members in New York City and around the world work collectively to achieve our conservation mission.
Position Objective: To maintain WCS equipment, facilities and grounds
Principal Responsibilities
  • Clean, patrol grounds, buildings, property, and structures of assigned areas.
  • Assist in the movement of WCS equipment and supplies.
  • Operate vehicles or other equipment such as snow throwers, leaf blowers, carpet extractors, vacuums, buffing machines.
  • Display proficiency and skills in use of tools associated with applicable fields

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