BCA Data Science student in Pune. I build end-to-end analytics and ML systems — and when I claim something works, I go build the test that checks whether it actually does. Data Analyst · ML Engineer · AI Trainer.
$ cat about.md
I'm a final-year BCA student specializing in Data Science at Sri Balaji University, currently completing a Cloud Application Developer internship (AWS, SQL, PySpark). Outside of coursework I build full projects — cleaning the data, training the models, and shipping something a non-technical person could actually use.
My most recent project is a controlled benchmark for evaluating LLM safety across nine dimensions. The part I'm proudest of isn't the benchmark itself — it's that I didn't just trust my own scoring system. I hand-labeled real model responses, measured how well an AI judge agreed with my own judgment, and reported the honest result even when it wasn't flattering.
$ ls ./projects
A controlled benchmark evaluating AI responses across 9 dimensions — instruction following, factuality, relevance, bias, toxicity, refusal quality, prompt injection resistance, hallucination, and consistency — run entirely on free-tier APIs. Includes a 2-model LLM-judge ensemble, a judge calibration test, and a human-agreement study measured with Pearson/Spearman correlation and quadratic weighted kappa. Mid-project, diagnosed and recovered from a live Groq model deprecation without invalidating prior results.
A production-style churn analysis on a 7,000+ row Telco dataset: SQL views, data-quality checks, cross-validation, cost-sensitive thresholds, and a human-review dashboard. The balanced model was selected on business trade-offs, not just accuracy.
Six automated workflows (n8n + GPT-4) covering onboarding, leave management, sentiment analysis, policy Q&A, resume screening, and a WhatsApp HR assistant — including a PDF-parsing resume screener with automated Slack alerts and Google Sheets logging.
A Streamlit web app that detects the language of input text in real time — built to ship something small and usable end-to-end, not just live in a notebook.
$ cat skills.json