Bayesian Statistics Expert Problem Designer

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 DAngelo Larry Summers and Jack Dorsey.

Position: Computational Bayesian Statistics and Applied Mathematics Expert
Type: Contract
Compensation: $70$100/hour
Location: Remote
Commitment: 1520 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 1520 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 2030 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

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PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.