Data-Scientist passionate about making meaningful contributions to the development of complete data engineering solutions by following tried and tested key steps: technical formalization of the business needs, database creation (QC, selection and labeling), data preprocessing, algorithms development and implementation, model performance evaluation, deployment in production and even continual learning of AI machines. Commercially oriented and capable of executing the best practices in refocusing business landscape to address evolving customer expectations through data engineering interventions.