Environmental Science Expert - Remote
YO AI Labs · United States · 2026-11-07
About this role
STEM & Scientific AI Expert
Location: Global, Fully Remote
Job Type: Contractor (~15 hours per week)
Schedule: Flexible
Job Summary
We are seeking STEM and scientific-domain experts to support AI training through complex problem-solving, scientific reasoning, data analysis, and Python-based coding. This is a coding-heavy role requiring experience with coding agents and the ability to evaluate AI-generated technical solutions.
Areas of Expertise
• Chemistry, Biology, Mathematics, and Physics
• Earth Science, Geoscience, and Environmental Science
• Robotics and related scientific or quantitative fields
Key Responsibilities
• Solve complex scientific and mathematical problems within your expertise.
• Use Python or other programming languages for calculations, simulations, and data analysis.
• Review AI-generated solutions for scientific and technical accuracy.
• Identify reasoning errors, incorrect assumptions, and missing constraints.
• Validate solutions against project requirements.
Required Qualifications
• Strong expertise in at least one relevant STEM discipline.
• Practical programming experience, preferably with Python.
• Strong analytical, scientific, and quantitative reasoning skills.
• Experience using coding agents in your workflow.
• Familiarity with tools such as NumPy, SciPy, pandas, SymPy, Jupyter, or relevant scientific libraries is beneficial.
Relevant expertise may come from academic research, industry, teaching, engineering, or independent technical work. A specific degree or minimum number of years of experience is not required if expertise can be demonstrated.
Selection Process
• Submit an application and complete screening questions.
• Complete an approximately 30-minute AI interview.
• Complete the hiring manager review.
Availability
Candidates should be ready to start promptly, with the first task expected within 24–48 hours after onboarding.
Originally posted on Himalayas
Skills asked for
- python
- numpy
- pandas
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