Data Scientist Data Scientist with expertise in Python, Machine Learning, Generative AI, and NLP. Skilled in building AI-driven applications using Hugging Face, Langchain, and Groq. Proven ability to design and deploy models for real-world applications, including predictive analytics and conversational AI. Greater Noida, India linkedin.com/in/md-harish-sarwar- github.com/harishsarwar EDUCATION Intermediate with 61% SMD College 01/ - 01/ , Gopalganj, Bihar Bachelor of Technology with 7 CGPA Greater Noida Institute of Technology 07/ - 07/ , Greater Noida WORK EXPERIENCE Python Intern Integration IT services PVT.LTD, Bhopal 05/ - 07/ , Performed data preprocessing, exploratory data analysis, and visualizations using Pandas, NumPy, Matplotlib, and Seaborn. Developed and deployed machine learning models for predictive analytics and classiﬁcation tasks using Scikit-learn and TensorFlow. Generated actionable insights and reports for stakeholders. TECHNICAL SKILLS Languages - Python, SQL AI &amp; Machine Learning - Generative AI, LLMs, NLP, Machine Learning, Deep Learning Libraries - Flask, Streamlit, Scikit-learn, Pandas, NumPy, TensorFlow, HuggingFace Technologies &amp; Tools - Langchain, Vector Databases (FAISS, ChromaDB), Groq, Gemini Business Intelligence Tool - Power BI PERSONAL PROJECTS News Article Summarization Developed a Streamlit-based application for retrieving, summarizing, and generating news articles using Groq&#039;s LLM and DuckDuckGo Search API. Integrated Newspaper4k for content extraction and Langchain for NLP tasks like summarization and article drafting. Enabled asynchronous processing with nest_asyncio and managed environment variables using python-dotenv. Technologies used: Python, Streamlit, Groq LLM, Langchain, DuckDuckGo API, Newspaper4k, dotenv, nest_asyncio. Medical Chatbot Developed a Streamlit-based medical chatbot leveraging Hugging Face&#039;s LLM and FAISS for vector search and response generation. Used HuggingFaceEmbeddings to embed medical data and implemented similarity search with FAISS for accurate query matching. Integrated the HuggingFaceEndpoint for generating conversational responses based on retrieved document context and user queries. Technologies used: Python, Streamlit, FAISS, Hugging Face LLM, sentence-transformers, HuggingFaceEmbeddings. Bangalore Real Estate Price Prediction Developed a ﬁne-tuned machine learning model to predict real estate prices in Bangalore based on location, BHK, area, and bathrooms. Fine-tuned the model on cleaned and preprocessed data to enhance prediction accuracy. Built an interactive user interface using Flask for seamless real-time predictions. Technologies: Python, Machine Learning, Flask, Scikit-learn, Pandas, NumPy, Matplotlib. CERTIFICATES Data Science | Python | SQL | Streamlit Responsibilities