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

mercor; United States; Remote; USD 96,000 - 138,000; Full time

Job summary

Mercor offers a remote contract role focused on computational Bayesian statistics and applied mathematics. The expert will design challenging problems, utilize software libraries, and validate solutions with AI models in a scientific computing context.

The position requires MS/PhD in a STEM field and strong Python skills, with proficiency in PyMC or FEniCS. Remote work with a commitment of 15–20 hours per week is expected.

Qualifications

• 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.

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.

Skills

Python programming

Independent work

Problem design

Linux/Unix familiarity

Education

MS/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.