I am a Computer Engineering graduate from Delhi Technological University with strong experience in data analytics, machine learning, and applied AI.
I build predictive models, perform exploratory data analysis, and develop data-driven applications using Python, SQL, Scikit-learn, TensorFlow, Tableau, and Streamlit.
View ResumeDesigned and published an interactive Power BI dashboard to analyze e-commerce revenue, profit trends, customer behavior, and category performance for data-driven decision-making.
The dashboard enables stakeholders to track KPIs, identify seasonal profit trends, evaluate category-level profitability, and optimize business strategy.
Built an end-to-end data analytics project analyzing Air Quality Index (AQI) trends across Indian cities. Cleaned and preprocessed raw air quality data using Python, stored and transformed data in a cloud-based PostgreSQL database, and designed an interactive Power BI dashboard.
The dashboard features dynamic AQI gauges, pollutant severity comparison, time-series trend analysis, and AQI category distribution with city, month, and year slicers. Focused on proper data modeling using DAX measures and calculated columns to ensure accurate filtering and real-world analytical insights.
Analyzed 300+ patient clinical records to identify key cardiovascular risk factors and built ML models achieving ~85% accuracy for early risk detection.
GitHub
Built a regression-based ML system on 1,000+ Glassdoor job listings with feature engineering and Random Forest achieving lowest error (NRMSE: 17.6).
GitHub
Built a modern, responsive news dashboard using Next.js and Tailwind CSS, designed for role-based access, analytics, and payout management.
Features include Google OAuth authentication, real-time news ingestion, author-level analytics, PDF/CSV exports, inline payout calculations, and dark/light mode with persistence.
Performed end-to-end churn analysis using Python, SQL, and Tableau, identifying customer segments with churn rate over 51%.
Built a GPT-powered DSA Chat Assistant that helps users understand LeetCode problems through guided hints, key concepts, and thought-provoking questions instead of direct solutions.
The application validates problem links, enforces structured responses, and encourages independent problem-solving using modern LLM workflows with a clean, interactive chat UI.
📧 hemangkrish7@gmail.com
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