Applied Mathematics Specialist - Fully Remote | Upto $100/hr

mercor; San Francisco (CA); Hybrid; GBP 16,000 - 21,000; Full time

Job summary

Mercor connects elite creative and technical talent with AI research labs. We seek a Computational Bayesian Statistics and Applied Mathematics Expert for a remote contract role, aligning scientific problem design with state-of-the-art AI models.

You will design challenging computational tasks, implement with PyMC/FEniCS, and validate solutions using Python in Linux environments. Availability 15–20 hours per week is required, with independence and iterative refinement emphasized.

Qualifications

• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent).
• Proficiency with PyMC, FEniCS or similar scientific libraries.
• Strong Python skills for problem setup and validation.
• Ability to work independently and refine problem designs.
• Comfortable in a Linux/terminal environment with remote compute sandboxes.
• Available for 15–20 hours per week.

Responsibilities

• Design challenging computational problems to test AI capabilities on scientific tasks.
• Develop problems requiring specialized scientific software for simulations and experiment design.
• Refine problems through iterative testing against 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.

Skills

Python

Problem design

Independent work

Linux / Unix

Remote compute sandbox

Education

MS or PhD in STEM

Tools

PyMC

FEniCS

Job description

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 Bayesian Statistics and Applied Mathematics Expert Type: Contract Compensation: $70–$100/hour Location: Remote Commitment: 15–20 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 15–20 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.