Shreeya Agarwal

I’m a data-driven IT graduate with hands-on industry experience in Python, SQL, Power BI, and machine learning. I focus on cleaning and analyzing complex datasets, building deployable predictive models, and turning results into dashboards that surface actionable business insights.

As a Python Developer Intern at HCLTech, I build domain-focused solutions for Healthcare & Pharma using Python and SQL, and I contribute with React in an agile environment. I work within cross-functional teams to translate real requirements into reliable, maintainable data and app features.

Previously, as a Technology Intern at Emerson, I engineered a C# parser to convert deeply nested JSON structures into report-ready CSVs, eliminating manual data wrangling. I also built an interactive Power BI dashboard with DAX measures to track key technology department KPIs and trends, and I designed and deployed an AI Document Summarizer using a RAG (Retrieval-Augmented Generation) pipeline.

My projects reflect how I like to work end-to-end: the SteamMarketIntelligence Platform uses Python, XGBoost, SHAP, FastAPI, React, and Docker to predict game commercial tier and review reception from 53K+ cleaned Steam listings, reaching a macro-F1 of 0.58 (3x majority-class baseline). I’ve paired performance with explainability using SHAP and deployed a FastAPI backend through a single REST endpoint. I’ve also built a HeartDiseasePrediction model with a KNN classifier from scratch, achieving 87% accuracy after hyperparameter tuning and improving data quality with categorical median imputation.