About the position
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 Statistics and Applied Mathematics Expert (R, Python, and Matlab/Scilab) Type: Contract Compensation: $70–$90/hour Location: Remote Commitment: 15–20 hours/week Role Responsibilities Design challenging computational problems to test AI systems' ability to solve scientific and engineering tasks. Develop problems requiring skilled use of specialized statistical , mathematical , or scientific software packages . Test and refine problems against state-of-the-art AI models to achieve target difficulty. Collaborate with AI research teams to improve problem setups and solution validators. Work independently in a Linux/terminal environment with remote compute sandboxes . Qualifications Must-Have Graduate-level training in statistics, applied mathematics, or a relevant STEM field. Proven proficiency with at least one specialized statistical, mathematical, or scientific software package. Strong Python skills. Ability to work independently and refine problem designs based on feedback. Available for at least 15–20 hours per week . Preferred Experience across multiple computational domains or specialized software packages. 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.
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