Himalayas · Partner listingSTEM Expert (MSc./PhD)
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⌖ WorldwideSalary not providedRemoteContract · Not specified
Source: Himalayas ↗
Location & working arrangementWorking arrangement is supplied by the provider. Check the original advert for attendance and travel requirements.
Provider location / applicant eligibility: Worldwide
About the role
STEM Expert
Pay: $60–$120/hour
Location: Global, fully remote
Job Type: Contractor (~15 hours per week)
Schedule: Flexible—you choose the hours and days you work, including weekends if desired
We are looking for highly skilled STEM and scientific-domain experts to contribute to an AI training project involving technical problem-solving, scientific reasoning, data analysis, and Python.
The work involves solving, reviewing, and validating challenging problems within your area of expertise. A representative task may require analyzing a scientific or mathematical problem, developing a rigorous solution, using Python to perform calculations or simulations, and evaluating whether an AI-generated answer is technically correct.
This is a very coding heavy role. Candidates but have experience using coding agents in their workflow.
Candidates are not expected to be experts across every STEM discipline. We are looking for deep expertise in at least one of the following areas:
Chemistry
Biology
Mathematics
Physics
Earth Science / Geoscience / Environmental Science
Robotics
Adjacent scientific or quantitative disciplines may also be considered where the candidate's expertise is directly relevant.
What You’ll Work On
Solve complex scientific, mathematical, or technical problems within your domain of expertise.
Review AI-generated solutions for factual, mathematical, and scientific correctness.
Identify incorrect assumptions, reasoning errors, missing constraints, and subtle technical mistakes.
Required Qualifications
Strong expertise in at least one relevant STEM or scientific domain.
Practical proficiency with Python or other coding languages.
Strong scientific, mathematical, or quantitative problem-solving ability.
Relevant Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries. No particular Python library is mandatory.
Expertise may come from academic research, industry, teaching, engineering, independent technical work, or other demonstrated experience. A specific degree or number of years of experience is not strictly required if you can demonstrate strong expertise in your field.
Process
Apply to the role and complete the screening questions.
Complete an AI interview of approximately 30 minutes.
Complete the hiring manager review.
Compensation Structure
Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.
Minimum submission requirements apply.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.
Originally posted on Himalayas
Skills mentioned in the listing
PythonData analysisPandasNumPy
Recognised skills are extracted from the supplied description using canonical names and aliases. They are mentions, not verified essential requirements. Check the source advert for the employer’s full requirements and location restrictions.
Why these skills appear
Python · mentioned
t involving technical problem-solving, scientific reasoning, data analysis, and Python. The work involves solving, reviewing, and validating challenging problems within your area of expertise. A representative task may r
Data analysis · mentioned
AI training project involving technical problem-solving, scientific reasoning, data analysis, and Python. The work involves solving, reviewing, and validating challenging problems within your area of expertise. A repres
Pandas · mentioned
ative problem-solving ability. Relevant Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries. No particular Python library is mandatory. Expertise may come from academic
NumPy · mentioned
al, or quantitative problem-solving ability. Relevant Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries. No particular Python library is mandatory. Expertise may come