Remote Bayesian Statistics & AI Problem Designer

Mercor; Paris; Sur place; EUR 96 432 - 137 760; Temps partiel

Résumé du poste

Mercor is seeking a Computational Bayesian Statistics and Applied Mathematics Expert. This role offers remote work, focusing on designing and refining computational problems for AI testing. Applicants should have a graduate-level STEM background and proficiency in Python and scientific software.

The position requires availability for 15–20 hours/week, with compensation set between $70 and $100 per hour, emphasizing independence and iterative improvement in problem design.

Qualifications

• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent).
• Proven proficiency with at least one scientific software library.
• Strong Python skills for writing problem setups and solution validators.

Responsabilités

• Design challenging computational problems to test AI capabilities.
• Develop problems requiring specialized scientific software for simulations.
• Refine problems through iterative testing against AI models.

Connaissances

Python

Scientific software proficiency

Linux/terminal environment

Formation

Graduate-level STEM training (MS, PhD, or equivalent)

Outils

PyMC

FEniCS

Description du poste

Mercor is seeking a Computational Bayesian Statistics and Applied Mathematics Expert. This role offers remote work, focusing on designing and refining computational problems for AI testing. Applicants should have a graduate-level STEM background and proficiency in Python and scientific software.

The position requires availability for 15–20 hours/week, with compensation set between $70 and $100 per hour, emphasizing independence and iterative improvement in problem design.