Aravind M

IT Analyst with 5 years of experience in Proactive Problem Management and SCCM Imaging at HCLTech, managing large-scale operational data and driving process automation. Recently transitioned into Data Science with hands-on experience in machine learning, deep learning, streamlit dashboards, web scraping, and cloud-based data workflows. Skilled in Python, SQL, and Power BI with multiple projects involving real-world datasets and business use cases. Seeking entry-level roles in Data Science, Analytics, or ML to apply analytical rigor and build data-driven solutions.

• Google Cloud Digital Leader (GCP)
• Oracle Cloud Infrastructure: Foundation Associate, AI Foundations, Data Foundations
• Data Science & AI Course – GUVI (IIT Madras affiliated, Ongoing)

Movie Recommendation & Query RAG System, Built a Retrieval-Augmented Generation (RAG) system using LangChain, FAISS, and OpenAI to handle natural language movie queries (e.g., recommendations, release years). Extracted and preprocessed data from MongoDB and transferred to PostgreSQL using Psycopg2 and SQLAlchemy. Created semantic and structural AI agents capable of handling both vector and SQL queries. Deployed a user-friendly Streamlit UI to query the system and visualize results. Bus Schedule Scraper & Streamlit Dashboard, Scraped real-time government bus data from RedBus using Selenium. Preprocessed and stored data in PostgreSQL for downstream reporting and analysis. Built a Streamlit interface for business analysts and tech users to generate reports or perform custom filtering. Electricity Consumption Forecasting (ML), Collected household electricity usage and external weather datasets. Cleaned data, analyzed outliers, analyzed skewness/kurtosis, and enriched it with additional features. Trained regression models to forecast future electricity demand with performance evaluation metrics. Chicago Crime Analysis in Power BI, Cleaned, transformed, and visualized real crime data from Chicago using Power BI. Built maps (Choropleth, Geo JSON), slicers, drill-downs, and trend charts. Created comprehensive interactive dashboards for seasonal, location-based, and crime-type analysis.