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Data Science with 1+ years in Generative AI & Machine Learning
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Assessing your cultural and operational fit
Data Science graduate with 2 years of internship experience developing Generative AI, NLP, Machine Learning, and intelligent automation solutions across automotive, healthcare, research, and technology domains. Experienced in building LLM-powered applications, AI agents, RAG systems, document intelligence solutions, and end-to-end AI workflows using Python, LangGraph, Docker, APIs, and cloud technologies. Strong background in designing scalable AI systems, integrating data-driven workflows, and delivering solutions that solve real-world business problems.
Amrita University
Integrated Master's in Data Science · Data Science
August 1, 2021 – June 30, 2026
Daimler India Commercial Vehicles (DICV)
Data Science Intern
January 1, 2026 – June 1, 2026
Chennai, Tamil Nadu, India
Care Revenue
Product & Technology Innovation Intern
June 1, 2025 – September 1, 2025
Thiruvananthapuram, Kerala, India
The Algorithm
Software Developer Intern
October 1, 2024 – May 1, 2025
India
Indian Institute of Management Kozhikode (IIMK)
Data Science Intern
May 1, 2024 – August 1, 2024
India
AI Claim Automation Pipeline
June 24, 2026 – Present
Built an intelligent document processing pipeline for information extraction, validation, summarization, and structured data generation from healthcare claim documents using NLP and LLM-based workflows.
RAG-based Document QA System
June 24, 2026 – Present
Developed an end-to-end Retrieval-Augmented Generation (RAG) system using LangChain, FAISS, vector embeddings, semantic search, and LLMs for enterprise document retrieval and contextual question answering.
Myocardial Infarction Detection using 3D-FMMECG
June 24, 2026 – Present
Developed and evaluated machine learning models for myocardial infarction detection using 3D feature representations, incorporating signal preprocessing, feature engineering, and classification techniques.
Financial Risk Prediction System
June 24, 2026 – Present
Built predictive machine learning models for financial risk assessment using feature engineering, preprocessing, model training, evaluation, and classification techniques.
Cultural Fit Analysis
The candidate's project diversity, spanning healthcare, finance, and general AI applications, indicates a broad interest and adaptability, which are positive indicators for cultural fit. The academic projects and multiple internships suggest a proactive and learning-oriented individual. The experience in collaborative environments (e.g., 'Collaborated with engineering teams') also points to a team-player mindset. The target role of Data Science aligns well with the candidate's education and experience.
Soft Skills & Operational Fit
The candidate's resume highlights problem-solving, analytical thinking, critical thinking, communication, collaboration, cross-functional teamwork, adaptability, and fast learning. These soft skills are crucial for a senior data scientist role, indicating a good operational fit for complex, collaborative projects. The experience in translating business requirements into analytical systems further supports this.