Environmental Scientist ( Freelancer)
Soul AI · Remote · remote · Posted 36d ago
Undisclosed2–6 yrsfulltimeSourced from
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About this role
We specialize in delivering high-quality human-curated data, AI-first scaled operations services, and more. We are seeking an Environmental Scientist (freelancer) to join our team and contribute to our AI-driven environmental research initiatives. This is a remote, flexible opportunity to work on impactful projects, applying scientific knowledge to enhance AI systems focused on environmental sustainability. Develop and evaluate models that predict environmental outcomes, focusing on sustainability, pollution, and natural resource management. Annotate and assess AI-generated content related to environmental issues, ensuring it aligns with scientific accuracy and relevance. Collaborate with cross-functional teams to integrate scientific findings into AI-based solutions for real-world environmental challenges. Ensure the application of environmental standards and regulations in AI projects. Provide feedback on AI responses to improve the quality and accuracy of environmental-related educational content. Strong knowledge of environmental regulations, sustainability practices, and environmental data analysis. Experience with data analysis tools and environmental modeling. Familiarity with AI and machine learning concepts is a plus. Excellent problem-solving skills and the ability to work in a collaborative environment. Strong communication skills and the ability to explain complex scientific concepts clearly. Opportunity to contribute to the advancement of AI technology.
Key Responsibilities:.
Conduct research and analyze environmental data to support AI-driven environmental projects.
Required Qualifications:.
Bachelors or Masters degree in Environmental Science, Ecology, or a related field.
Why join us.
Fully remote and flexible work schedule.
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About Soul AI
Soul AI
Emerging Technologies
₹9.4L PA avg
Avg at Soul AI
About
Soul AI provides advanced AI solutions, specializing in the curation of specialized datasets to enhance the performance of large language models globally.
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