PhD Mathematician or Statistician, AI Expert (Remote, US)

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StatisticianData & AI

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Quick Summary

Key Responsibilities

Assess mathematical and statistical problems, reasoning tasks, and AI-generated outputs for accuracy, logical consistency, and mathematical rigor. Identify gaps in proofs, unjustified assumptions,

Requirements Summary

Assess mathematical and statistical problems, reasoning tasks, and AI-generated outputs for accuracy, logical consistency, and mathematical rigor. Identify gaps in proofs, unjustified assumptions,

Technical Tools

StatisticianData & AI

What We Offer

~1 min read

Requirements

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PhD in Mathematics, Applied Mathematics, Statistics, Operations Research, or a closely related discipline.
Senior-level academic or research experience, such as:

Faculty appointment at a recognized university.
Principal Investigator (PI).
Staff Scientist or Senior Scientist.
Equivalent senior research position at a university, national laboratory, or established research organization.

Deep specialization in at least one of the following domains:

Mathematical Analysis and Partial Differential Equations (PDE).
Algebra and Number Theory.
Geometry and Topology.
Probability Theory and Statistics.
Applied Mathematics.
Mathematical Optimization and Operations Research.
Computational Mathematics.
Advanced Statistical Modeling and Inference.

Strong peer-reviewed research publication record.
Recognition through competitive academic fellowships, research grants, awards, or other notable research achievements is an added advantage.
Hands-on experience using Large Language Models (LLMs) and AI tools in academic, mathematical, or research workflows.
Strong analytical and critical-thinking abilities, with the ability to identify subtle mathematical errors and evaluate complex proofs.
Excellent written communication skills and the ability to provide precise, structured, and technically sound feedback.
Must be currently based in the United States.

Responsibilities

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→Expert Evaluation: Assess mathematical and statistical problems, reasoning tasks, and AI-generated outputs for accuracy, logical consistency, and mathematical rigor.
→Identify gaps in proofs, unjustified assumptions, incorrect derivations, flawed reasoning, and invalid generalizations in AI-generated solutions.
→Problem Design: Develop precise, challenging, research-level mathematical and statistical problem statements that reflect real-world academic and research challenges.
→Reference Solutions & Proofs: Create detailed reference solutions and rigorous mathematical proofs that establish clear standards for correctness and logical reasoning.
→Benchmark Development: Design advanced mathematical and statistical problems, evaluation datasets, and benchmarks within your area of specialization to assess AI model capabilities.
→Research Assessment: Distinguish mathematically sound arguments from plausible-sounding but incorrect solutions, ensuring high standards of scientific and analytical accuracy.
→Research Collaboration: Work with AI researchers and subject matter experts across related disciplines to establish evaluation methodologies and improve model reasoning.
→Feedback & Calibration: Translate specialized mathematical knowledge and expert judgment into structured evaluation criteria, detailed feedback, and measurable quality standards.

Engagement will be on an independent contractor basis.
The position is fully remote and offers flexibility to complete assignments according to your own schedule and project requirements.
Project timelines may be extended, shortened, or concluded early depending on business requirements and individual performance.
The engagement will not require access to confidential or proprietary information belonging to any current or former employer, client, university, or research institution.
Payments will be processed weekly through Stripe or Wise based on services rendered.
H-1B and STEM OPT visa holders cannot be accommodated for this opportunity.