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Data Science with less than a year in Machine Learning, Deep Learning & NLP.
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Assessing your cultural and operational fit
Highly motivated and results-driven Artificial Intelligence and Data Science undergraduate student with strong academic performance (CGPA: 9.33). Possesses hands-on experience in developing AI/ML applications, including Retrieval-Augmented Generation (RAG) for document processing, sentiment analysis, and deep learning for medical image classification. Proficient in Python, R, Java, SQL, and various data science libraries and tools, eager to contribute to innovative data-driven projects.
Nitte Meenakshi Institute of Technology
B.E. · Artificial Intelligence and Data Science
August 1, 2022 – June 30, 2026
AI Document Assistant
June 1, 2022 – June 1, 2026
Developed an end-to-end Retrieval-Augmented Generation (RAG) application for querying and summarizing PDF documents using Large Language Models. Implemented document chunking, embedding generation, semantic retrieval, and vector storage using Sentence Transformers and ChromaDB. Integrated Gemini API with prompt engineering and conversational memory for context-aware question answering. Built an interactive Streamlit interface enabling document upload, retrieval-based search, and grounded response generation.
View ProjectFlipkart Review Sentiment Analysis
June 1, 2022 – June 1, 2026
Built an end-to-end sentiment analysis pipeline on Flipkart product reviews using Kaggle API for automated data ingestion and NLP preprocessing. Performed sentiment classification using TextBlob and Hugging Face transformer models to categorize reviews as Positive, Negative, or Neutral. Developed an interactive Power BI dashboard to visualize sentiment trends, customer feedback patterns, and product insights.
View ProjectBone Fracture Detection using Deep Learning
June 1, 2022 – June 1, 2026
Designed and implemented a deep learning-based medical image classification system to detect bone fractures from X-ray images. Evaluated multiple CNN architectures including ResNet50, EfficientNetB0, VGG16, MobileNetV2, and a custom CNN using transfer learning techniques. Applied image preprocessing, augmentation, and model optimization strategies, achieving 96% classification accuracy with ResNet50.
View ProjectR Programming
Coursera
June 1, 2026 – Present
Advanced Python for AI Applications
Dalivk Apps
June 1, 2026 – Present
Cloud Computing
NPTEL
June 1, 2026 – Present
Introduction to Statistics
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong alignment with the target role of Data Science, covering diverse areas like NLP, computer vision, and LLMs. Involvement in community service and language certification (JLPT N5) indicates a proactive learning attitude and broader interests, which can contribute positively to cultural fit. The breadth of skills and tools used across projects suggests adaptability and a willingness to explore different technologies.
Soft Skills & Operational Fit
The candidate's involvement in community service and leadership roles (Bharat Scouts & Guides, NSS) suggests good soft skills, including teamwork, discipline, and commitment. These traits are valuable for operational fit in a collaborative environment. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.