Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP) Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift. Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc. Ability to understand tools used by data scientist and experience with software development and test automation. Good understanding of advanced AI/ML algorithms & their applications Applications and Digital Automation Solutions, Low Code /No Code and Automation Platforms, designing API's and exposure to DevOps, React/Angular, containers, building visualization layer. Knowledge of self-service analytics platforms such as Dataiku/ KNIME/ Alteryx will be an added advantage. MS Excel knowledge is mandatory. Familiarity with Life Sciences is a plus