Research Scientist - Computational Mathematics (Scientific Coding / AI Evaluatio

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

Role Overview

We are looking for a highly analytical and research-driven individual with a strong background in Computational Mathematics to contribute to advanced AI evaluation initiatives.

In this role, you will design and solve research-grade quantitative problems, supporting the development and evaluation of next-generation AI systems. You’ll work at the intersection of scientific computing, mathematical modeling, and AI reasoning, contributing to high-impact projects with leading AI organizations.

Responsibilities:

Quantitative Problem Design and Solutioning:

• Design and develop research-level or graduate-level mathematical problems involving scientific computing and programming (Python)
• Define clear problem structures, including categories, tags, and difficulty levels
• Solve complex problems using rigorous mathematical and computational methods, ensuring accuracy and logical consistency

Quality Assurance & Collaboration:

• Actively participate in two-tier reviews, meticulously evaluating both accuracy of problems and solutions.
• Collaborate effectively with reviewers and team leads, demonstrating a proactive approach to incorporating feedback, refining content, and enhancing overall quality promptly.

Commitments Required: 8 hours per day with an overlap of 4 hours with PST.

Employment type: Contractor assignment (no medical/paid leave)

Duration of contract: 4 weeks

Location: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Kenya, Nigeria,Turkey, Vietnam

Selection process: Home Assignment

Requirements

• PhD or PhD Candidate in Computational Mathematics, Applied Mathematics, or related field
• Strong background in numerical linear algebra, computational mechanics, or scientific computing
• At least one peer-reviewed publication in a relevant domain
• Proficiency in Python for scientific computing (e.g., NumPy, SciPy, or similar)
• Strong analytical thinking and problem-solving skills
• Ability to clearly document complex mathematical reasoning and solutions