At SymphonyAI, I led the design and deployment of ML and AI-driven analytics platforms for enterprise datasets with millions of records. I developed RAG pipelines and LLM-based systems that improved insight-generation accuracy by approximately 25%.
I build end-to-end real-time and batch data pipelines with Python, Spark, and Kafka, and train models for classification, forecasting, and recommendations. I also implement monitoring and evaluation frameworks that improve model reliability and reduce drift.
Previously at Google, I built data pipelines, analytics systems, ML workflows, and A/B testing frameworks, reducing pipeline latency by approximately 40%. At Microsoft, I developed ETL pipelines with Azure data services, reporting tools, and data-driven enterprise features.
Across 11+ years, I’ve translated business problems into scalable data science solutions and mentored data scientists and engineers on ML best practices and model deployment.
