Remote Computational Bayesian & Applied Mathematics Expert

Mercor; San Francisco (CA); Remote; USD 96,432 - 137,760; Part time

Job summary

Mercor is seeking a Computational Bayesian Statistics and Applied Mathematics Expert to work on challenging computational problems that test AI capabilities. The role is remote, offering contract compensation of $70–$100 per hour, with a commitment of 15–20 hours per week.

The ideal candidate will have serious qualifications in a STEM field (MS or PhD) and strong skills in Python and scientific software libraries. Opportunities for problem design and strategic collaboration are central to this position.

Qualifications

• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
• Proven proficiency with at least one scientific software library (e.g., PyMC, FEniCS).
• 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.

Responsibilities

• Design computational problems to test AI capabilities.
• Develop problems using specialized scientific software.
• Refine problems against state-of-the-art AI models.
• Collaborate on tasks requiring strategic thinking.
• Enhance problem designs based on feedback.

Skills

Graduate-level training in relevant STEM field (MS, PhD)

Proficiency with scientific software libraries (PyMC, FEniCS)

Strong Python skills

Comfortable in Linux/terminal environments

Education

Graduate-level training in relevant STEM field

Tools

PyMC

FEniCS

Job description

Mercor is seeking a Computational Bayesian Statistics and Applied Mathematics Expert to work on challenging computational problems that test AI capabilities. The role is remote, offering contract compensation of $70–$100 per hour, with a commitment of 15–20 hours per week.

The ideal candidate will have serious qualifications in a STEM field (MS or PhD) and strong skills in Python and scientific software libraries. Opportunities for problem design and strategic collaboration are central to this position.