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Assessing your cultural and operational fit
Full-stack development enthusiast and Computer Science Engineering undergraduate specializing in AI/ML, with hands-on experience building MERN stack applications and machine learning projects. Skilled in React.js, Node.js, Express.js, MongoDB, Python, and RESTful APIs, with experience in developing scalable web applications, real-time AI systems, and cloud-based deployments. Passionate about problem-solving, clean code practices, and creating impactful technology solutions.
Alliance University. Bangalore
B.Tech · Computer Science
December 4, 2022 – May 29, 2026
Achieved a perfect score, indicating comprehensive knowledge and practical proficiency in the assessed full-stack frontend development areas, including Redis and API integration.
Strengths
Limitations
Achieved a good score of 72%, demonstrating a strong grasp of core MERN stack technologies. The score suggests a solid foundation but also indicates some areas where deeper understanding or practical application could be enhanced.
Cultural Fit Analysis
The candidate exhibits strong technical aptitude and a positive psychometric profile, suggesting a good general cultural fit for a technically oriented, collaborative environment. The diversity of technical projects (full-stack web development, AI/ML) indicates intellectual curiosity and adaptability. However, the candidate's entire professional and academic background is in Computer Science and software development, making the 'Ass. HRM' target role a complete and fundamental mismatch for cultural and professional alignment.
Soft Skills & Operational Fit
The candidate scored well on the psychometric test (76.2%), indicating good logical reasoning, work attitude, stress handling, and team collaboration potential. Project participation (e.g., hackathon) further supports teamwork and problem-solving under pressure. However, there is no operational fit for an 'Ass. HRM' role, as all demonstrated skills and experience are technical.
Strengths
Limitations