Deepika Tanubudhi

Data Scientist @Enzymedica

Venice, FL, US

EnzymedicaAt Enzymedica, I spearheaded a Generative AI RAG pipeline to streamline research on health products and supplements, which boosted research productivity by 40%. I also engineered demand forecasting models (ARIMA, Prophet, XGBoost) that reduced overstock by 20% and improved inventory planning by 15%. I used complex SQL queries with Hive and Presto to analyze sales and marketing data, improving campaign ROI by 15%. I containerized and deployed AI services with Docker and AWS EKS, which improved release efficiency by 30% and ensured the scalability of consumer health product forecasting systems. Additionally, I developed a multilingual NLP pipeline that increased demand prediction accuracy by 25% across five markets. I integrated sales data into Tableau dashboards using Python and SQL, cutting reporting latency by 70% and enabling faster business insights. I also automated ETL, model monitoring, and retraining workflows with Airflow, Unix scripting, and AWS Lambda, which reduced model drift by 35%. Finally, I leveraged Apache Spark to process customer transaction and sales records, cutting batch data processing time by 50%.

Utah State University

Master's in Information Systems