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Why this grade This listing scored 30/100, which is an F. It lost the most ground on freshness. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
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-15 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
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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)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
- For any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas
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Where this listing came from
- 08 Jul 2026 Himalayas first sighting
Seen on 1 board over 0 days.