STEM Scientific Reasoning Expert

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. It connects skilled contributors with opportunities to help shape how advanced AI systems reason, communicate, and perform technical work.

Creating an OpenTrain account is free. Through OpenTrain, you can build a profile that reflects your expertise, discover projects aligned with your skills, and apply in minutes.

About AI Training Work

AI training is the human side of building artificial intelligence. Experts review model outputs, create high-quality examples, and assess whether responses are accurate, well-reasoned, and supported by evidence.

In this role, your scientific and quantitative judgment will help improve how AI systems solve complex technical problems. The work is remote and flexible, making it possible to contribute from anywhere while building experience in a fast-growing technology field.

The Role

OpenTrain is seeking a STEM Scientific Reasoning Expert to support AI training through rigorous technical problem-solving and expert review. You will work within your strongest scientific or quantitative specialty, solve challenging problems, validate AI-generated solutions, and determine whether conclusions follow from sound reasoning and evidence.

The role combines subject-matter expertise with Python-based computation, simulation, data analysis, and careful evaluation of technical answers. Relevant expertise may include chemistry, biology, mathematics, physics, earth science, linguistics, robotics, or another demonstrated STEM discipline.

• Remote worldwide contractor opportunity
• Approximately 15 hours per week
• Flexible scheduling, including the option to work weekends
• Pay range of $50 to $100 per hour
• English-language work

What You'll Do

You will assess technical work carefully and produce clear, reproducible reasoning that can be used to improve AI system performance. Your reviews may involve equations, experimental results, datasets, technical diagrams, or scientific literature when relevant.

• Solve complex scientific, mathematical, and technical problems within your strongest domain.
• Review AI-generated solutions for factual, mathematical, and scientific correctness.
• Identify incorrect assumptions, reasoning errors, missing constraints, edge cases, and subtle technical mistakes.
• Develop clear, reproducible reference solutions that demonstrate the correct approach.
• Use Python for scientific computation, data analysis, simulations, and solution validation.
• Interpret equations, experimental results, datasets, technical diagrams, or scientific literature when relevant.
• Perform sanity checks and validate numerical or analytical results.
• Compare alternative approaches and explain whether the available evidence supports the conclusions.

Requirements

You should have deep expertise in at least one relevant STEM or scientific discipline and practical proficiency with Python. Strong candidates can solve complex quantitative or scientific problems, validate technical work, and communicate conclusions and corrections with precision.

A specific degree or fixed number of years of experience is not required when strong subject-matter expertise can be demonstrated. Relevant experience may come from academic research, industry, teaching, engineering, independent technical work, or another setting.

• Deep expertise in at least one STEM or scientific discipline.
• Practical Python proficiency for scientific computation, data analysis, simulations, or validation.
• Strong scientific, mathematical, or quantitative problem-solving ability.
• Ability to identify incorrect assumptions, missing constraints, edge cases, and technical reasoning errors.
• Experience developing rigorous, reproducible solutions to complex quantitative or scientific problems.
• Experience validating, reviewing, or troubleshooting technical work.
• Ability to explain complex technical concepts, solutions, conclusions, and corrections clearly and accurately.

Helpful Technical Background

Useful Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries, although no particular library is required. What matters most is the ability to use computation and analysis effectively for technical validation.

• Scientific computation
• Data analysis
• Simulation
• Numerical or analytical validation
• Technical solution review and troubleshooting

How to Apply

Apply through OpenTrain to be considered for this flexible AI training opportunity. Your work will contribute to the human-reviewed examples and evaluations that help modern AI systems become more accurate and scientifically reliable.

OpenTrain helps contributors grow an AI training portfolio around their skills and experience. Create a free account, complete your profile, and apply in minutes.