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 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