Sourodeep Das

Developed a healthcare ecosystem tool to optimize staff planning, admissions, discharge, and decision-making, enhancing operational efficiency and patient care through data-driven insights and automation. - Orchestrated seamless data extraction from heterogeneous sources including Big Query, S3, and Redshift databases. - Enforced meticulous data quality protocols and executed efficient preprocessing workflows to ensure integrity and usability. - Pioneered creation of robust time series forecasting models and classification models for precise predictions and data stratification. - Utilized advanced generative AI and LLM models, alongside expertise in data visualization and reporting, to uncover valuable insights for strategic decision-making and operational enhancement.

Collaborated with a Fortune 500 client to analyze market dynamics and enhance their Loyalty program. Conducted assessments to quantify the impact of Loyalty initiatives, resulting in data-driven recommendations that led to a 32% increase in engagement and revenue. - Designed and executed seamless data pipelines, prioritizing accuracy, and automating preprocessing for efficient analysis and informed decisions. - Enhanced model accuracy through data analysis, machine learning development, and iterative refinement, improving performance through continuous evaluation and Google Cloud Platform (GCP) deployment. - Led impactful client meetings, effectively communicating solution value and fostering productive collaborations. - Nurtured junior members through guidance, enhancing skills in a collaborative setting and contributing to team growth and development.

Led innovative Application development predicting Work Request success, boosting productivity by 75%. Employed NLP and Cloud Services for accurate data extraction, including Industry, Financial Year, and Amount Derivatives. Led cross-functional collaboration, ensured SDLC adherence, and addressed bugs timely in an agile environment. - Led end-to-end creation, enhancing user experience with Python and leveraging NLP for accurate data extraction using Named Entity Recognition (NER) via Cloud Services, resulting in bolstered predictions. - Developed a document classification model with PDF extraction, contributing to improved accuracy and efficiency in data processing. - Produced scalable code following SDLC, addressing bugs promptly to maintain application integrity and functionality. - Thrived in an agile setup, delivering high-quality results on schedule, and fostering continuous improvement and innovation.

Developed Pharma Co-Vigilance project using ML to forecast adverse events, suspect drugs, and case seriousness. Automated processes, reducing processing time by 95%. Proficiently utilized Python and REST API for streamlined operations. - Led data gathering and preprocessing efforts, ensuring comprehensive data acquisition and preparation to facilitate accurate analysis. - Developed the Pharma Co-Vigilance application using Python and REST API, collaborating with UI and Java teams to ensure seamless integration of machine learning functionalities. - Managed project tasks and workflows using JIRA, implementing SDLC methodologies for efficient development and timely delivery. - Collaborated closely with other teams to ensure the successful integration of machine learning functionalities into the application, fostering cross-functional collaboration and synergy.