➤ Designed and implemented end-to-end Machine Learning pipelines using Dataiku.➤ Built utilities such as Data Drift, Data Quality, and Model Monitoring Dashboards for ML pipelines to assist data scientists in enhancing model performance.➤ Operationalized 30+ models ranging across multiple use cases and algorithm types.➤ Migrated an end-to-end ML pipeline implemented on Databricks from Azure stack to AWS stack.➤ Developed a Data Quality Management (DQM) Framework using Python, Docker, and Azure DevOps.➤ Constructed a Power BI dashboard to provide customized and user-friendly DQM insights to end-users.➤ Maintained clear and comprehensive documentation for data pipelines, architecture, and best practices

➤ Performed depth estimation from RGB images using Conditional Generative Adversarial Networks (cGANs).➤ Developed a model capable of performing image-to-image translation from the RGB space to depth space, utilizing the pix2pix model as a reference for transfer learning