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 OverviewWe 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 consistencyQuality Assurance & Collaboration:Actively participate in two-tier reviews, meticulously evaluating both accuracy of problems and solutionsCollaborate effectively with reviewers and team leads, demonstrating a proactive approach to incorporating feedback, refining content, and enhancing overall quality promptlyCommitments 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 weeksLocation: Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Indonesia, Kenya, Nigeria,Turkey, VietnamSelection process: Home AssignmentRequirementsPhD 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