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Job description
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Computational Bayesian Statistics and Applied Mathematics Expert
Type:Contract
Compensation:$70–$100/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks.
Develop problems requiring the use of specialized scientific software for simulations and experiment design.
Refine problems through iterative testing against state-of-the-art AI models to achieve target difficulty.
Collaborate on creating tasks that require strategic thinking and efficient information extraction.
Work independently to enhance problem designs based on feedback and model performance.
Qualifications
Must-Have
Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
Proven proficiency with at least one scientific software library (PyMC, FEniCS, etc.).
Strong Python skills for writing problem setups and solution validators.
Ability to work independently and refine problem designs.
Comfortable in a Linux/terminal environment with remote compute sandboxes.
Available for at least 15–20 hours/week.
Preferred
Experience across multiple domains or tools.
Familiarity with benchmark or evaluation design.
Background in scientific teaching or exam/problem-set design.
Experience with computational reproducibility and containerized environments.
Application Process (Takes 20–30 mins to complete)
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Resources & Support
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Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.