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Het415/README.md

Het Prajapati

Data Scientist · ML Engineer · NLP & Agentic AI

LinkedIn GitHub Email Boston

MS Data Science @ Northeastern University. I build end-to-end ML systems; from ETL pipelines and predictive models to production-deployed LLM applications. Focused on retail analytics, agentic AI, and turning messy data into decisions.

Projects

ListingLens — Amazon Seller Intelligence Platform

Multi-stage NLP pipeline processing 250 reviews/product · BERT sentiment scoring · XGBoost return risk classifier (96.5% acc, 0.997 ROC-AUC) · RAG pipeline with FAISS + LLaMA 3 70B · Deployed on Railway + Vercel

Distributed Backtesting Engine — Algorithmic Trading

PySpark parallel framework · 123 strategies × 100 S&P 500 stocks · 12,300 backtests on 303K real market records · 5-step data governance pipeline · 9-panel Plotly BI dashboards

Spotify Breakout Predictor — Viral Music Classification

99.2% accuracy · 0.998 ROC-AUC · temporal + 5-fold cross-validation · TikTok views as dominant predictor (41% importance) · Interactive Streamlit dashboard

Stack

Languages · Python · R · SQL · Java · JavaScript

ML / AI · Scikit-learn · XGBoost · PyTorch · TensorFlow · HuggingFace · LangChain · FAISS · RAG Pipelines

Data Engineering · PySpark · ETL · Data Warehousing · Snowflake · MySQL · PostgreSQL

Deployment · FastAPI · Next.js · Railway · Vercel · AWS (CLF-C02)

Experience

Data Science Intern · Compatible Solutions (Jan 2025 – Jun 2025)

  • Built ETL pipelines processing 100K+ records with data governance for BI reporting
  • Improved predictive model accuracy by 20% over legacy system via feature engineering + hyperparameter tuning
  • Conducted A/B testing and delivered interactive dashboards for stakeholder decision-making

Data Science Intern · Yhills / IIT Hyderabad (Mar 2023 – May 2023)

  • Built ML models for H1N1 vaccine prediction (84% acc) and NYC taxi fare (RMSE $3.20)
  • Engineered 25+ features from temporal, geographic, and demographic data; improved performance by 30%
  • Communicated insights via visual dashboards for non-technical stakeholders

Currently Exploring

  • LLM applications & agentic workflows
  • Scalable ML systems & deep learning
  • Distributed data processing (Spark + cloud)

GitHub Streak

Pinned Loading

  1. listinglens listinglens Public

    AI-powered Amazon seller intelligence platform — BERT sentiment, XGBoost return risk prediction, and RAG chatbot grounded in real customer reviews.

    TypeScript 1

  2. algorithmic-trading-backtest algorithmic-trading-backtest Public

    Distributed trading strategy backtesting with PySpark - 12,300 backtests on 100 stocks

    Jupyter Notebook

  3. Spotify_predictor_enhanced Spotify_predictor_enhanced Public

    A Machine Learning tool to predict upcoming Spotify breakout artists using TikTok and Shazam data. Features a Random Forest backend and a Streamlit frontend.

    Jupyter Notebook