Remote Contract: Computational Bayesian & Applied Math Expert

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

Job summary

Mercor is seeking a Computational Bayesian Statistics and Applied Mathematics Expert to design and develop computational problems that test AI capabilities. This role requires a graduate-level education in a relevant STEM field and strong Python skills.

Work remotely for approximately 15-20 hours a week, collaborating on innovative AI projects. If you have a passion for science and expertise in scientific software libraries like PyMC or FEniCS, this is the perfect opportunity for you.

Qualifications

• Graduate-level training in a relevant STEM field.
• Proficiency with at least one scientific software library (PyMC, FEniCS, etc.).
• Strong Python skills for writings problem setups and solution validators.
• Independent work with problem designs based on feedback.

Responsibilities

• Design computational problems to test AI capabilities.
• Develop problems using specialized scientific software.
• Refine problems through iterative testing against AI models.
• Collaborate on strategic thinking tasks.

Skills

Graduate-level training in a relevant STEM field

Proficiency with scientific software libraries like PyMC or FEniCS

Strong Python skills

Ability to work independently

Comfortable in a Linux/terminal environment

Education

Graduate degree (MS, PhD, or equivalent research experience)

Tools

Scientific software libraries

Linux/terminal environments

Job description

Mercor is seeking a Computational Bayesian Statistics and Applied Mathematics Expert to design and develop computational problems that test AI capabilities. This role requires a graduate-level education in a relevant STEM field and strong Python skills.

Work remotely for approximately 15-20 hours a week, collaborating on innovative AI projects. If you have a passion for science and expertise in scientific software libraries like PyMC or FEniCS, this is the perfect opportunity for you.