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AI Engineer with less than a year in Python, Data Science & Web Development for AI-driven solutions.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Computer Science and Data Analytics student with a strong foundation in Machine Learning, Deep Learning, and Web Technologies. Proven ability to develop and deploy AI-driven applications, including conversational chatbots and prediction systems. Seeking to leverage analytical and technical skills to create innovative solutions in data science and AI.
Indian Institute of Technology, Patna
Bachelor of Science · Computer Science and Data Analytics
August 1, 2023 – June 30, 2026
AIRA – AI Conversational Chatbot
January 1, 2025 – January 1, 2026
Developed a full-stack AI chatbot using OpenAI API for real-time, context-aware conversations with response time under 2 seconds. Implemented JWT authentication and multi-session chat management with MongoDB, improving chat handling efficiency by 40%. Built a responsive UI using React.js and SCSS with dark/light mode, chat history, and message management features. Designed scalable backend APIs using Node.js and Express.js for efficient AI request processing and conversation storage.
Flight Price Prediction Web App
January 1, 2025 – December 1, 2025
Developed and deployed a machine learning web app to predict airline ticket prices using historical flight data and real-time user inputs. Performed preprocessing and feature engineering on 10K+ flight records, improving model performance by approximately 18%. Trained and optimized a Random Forest Regression model achieving 90%+ prediction accuracy with reduced prediction error. Integrated the ML model with a Flask backend and deployed the application on Render with automated GitHub-based updates.
Diabetes Prediction System
January 1, 2025 – June 1, 2025
Built a machine learning-based healthcare web app to predict diabetes risk using medical parameters such as glucose, BMI, insulin, and age. Trained and evaluated a classification model achieving 85%+ prediction accuracy after preprocessing and feature optimization. Designed a responsive frontend using HTML, CSS, and Bootstrap with real-time form validation, improving usability by nearly 40%. Implemented an end-to-end ML pipeline including preprocessing, model serialization using Pickle, Flask backend integration, and deployment-ready architecture.
Cultural Fit Analysis
The candidate's academic projects show a strong interest in AI and machine learning, aligning well with an AI Engineer role. The diversity of projects (healthcare prediction, flight price prediction, conversational AI) indicates adaptability and a broad interest in applying AI to different domains. The use of modern technologies like OpenAI API, MERN stack, and various ML/DL frameworks suggests a proactive approach to learning and adopting new tools. However, without professional experience, the cultural fit in a corporate environment is yet to be fully assessed.
Soft Skills & Operational Fit
The candidate demonstrates good problem-solving skills through their project descriptions, focusing on improving accuracy and efficiency. Their academic projects suggest an ability to work independently and deliver functional applications. However, without psychometric test results or interview data, it's difficult to assess stress handling, team collaboration, or specific work attitudes.