Implemented t-SNE and PCA on complex chemical datasets, resulting in a 30% reduction in feature space while retaining 95% of the variance, enabling faster and more efficient data processing.

Developed an intuitive data visualization tool using React, Python RESTful APIs that allowed non-technical stakeholders to interact with t-SNE and PCA outputs, leading to a more informed decision-making process.

Compiled and mined various data sources, leading team efforts to enhance predictive model accuracy by 20%.

Developed and maintained interactive Spotfire dashboards that visualized critical business metrics for executive decision-making, resulting in an average weekly time savings of 2 hours.

Enhanced SQL queries, increasing productivity by 40% for faster data retrieval and heightened analysis efficiency.

Collaborated to design & implement microservices-based pipeline, cutting ETL time by 30% and enhancing data accuracy.

Led the optimization of data storage, reducing data processing time by 25% & enhancing operational efficiency.

Managed huge datasets with MongoDB (NoSQL), improving query performance by 40% for efficient data processing.

Implemented "human in the loop" approach, reducing forecasting errors by 15% and enhancing decision-making.

Designed robust APIs for model integration, resulting in a 20% improvement in scalability & providing user-friendly access to system.

Automated model training, deployment using Apache Airflow, and collaborated cross-functionally to deliver impactful data solutions.