Hi, I'm Aradhya Agrawal.

Designing and deploying AI agents and production-grade LLM systems. Building intelligent automation pipelines that bridge analytics and engineering.

• Optimized SQL across 70B+ rows in BigQuery, improving query performance by 80%.
• Built CLV, propensity (KNN), and logistic regression models — 3.2x lift vs random targeting.
• Led hypothesis testing across 100+ campaigns, lifting conversion by 15%.
• Supported ML-driven Media Mix Model, cutting inefficient spend by 20%.

• Automated ETL pipeline processing 20–40 GB/day to AWS S3.
• Engineered YOLOv3 defect detection model — cut manual inspection by 60%.
• Deployed Random Forest model on AWS — drove 9% sales increase.

• Designed state-level spatial data model — 50% faster query times.
• Built Airflow + PySpark pipelines ingesting 1M+ rows/day into BigQuery.
• Trip classification model (Random Forest + XGBoost) — 82% accuracy.

• Improved sales predictions by 12% — projected $5M revenue increase.
• Embedded lost sales prediction model into inventory management system.
• A/B tested vs baseline — reduced stockout errors by 15–20%.