Designed and developed analytics platform solutions to serve machine data for Diagnostics Department using DatabricksDesign the data ingestion pipeline receiving data on a scale of 500 million records per dayPerformed data quality checks and data testingBuild dashboard for monitoring pipelines and missing files in landing zone for Production. Creating triggers for anomalydetectionCollaborated with analysts and other stakeholders to understand data needs and requirements.Experience in engineering large-scale systems in a product environment and writing complex queries

Worked on several projects to enable Digitalization of Healthcare services including”Covid Home Self-test Kit”, urinalysis mobile appProcessing the image to be fed to the algorithms for making callouts. Checking theimage quality and validity.Training of the algorithm responsible for making callouts (Accuracy - 95 percent).Involved in experiment design, hypothesis testing, prototype development and finalproduct deliveryDesigning the backend services involving implementation of API Gateway, AzureFunctions, REST APIs, containerization of micro-services using docker in serverlessarchitectureSpearheading development of MLOps pipeline from scratch

Trained deep learning YOLOv3 model for detection of Siemens Multistix 10SG Reagent Strip involving data gathering and data annotation.Processing the image for recognition of various medical conditions by analysing the color change in respective reagent segments.Deploying a flask app in a linux based docker image.Framework used:- Darknet.

Developed a framework to create Content Management Systems on the fly to maintain third partydatabases using Ruby on Rails.