Data Scientist

Skills

Programming languages: Python R Excel(preparation and pivot charts) Python: Numpy Pandas sklearn pickle awswrangler and ml model deployments AWS: Lambda API Gateway S3 Athena Glue Sagemaker Service Catalog Cloudformation CodePipeline Docker: Dockerfile ECR docker commands Version Control: Git CodeCommit Visualization: Some knowledge on any visualization tools Nice to have Python: Oops concepts Flask API creations and security AWS: Fargate ECS EMR Proton CDK using python or node Sagemaker Studio Docker: DockerCompose Data Preparation: Dataiku

Description

A proactive candidate primarily from Analytical background with good knowledge in Python.

Should posses ability to learn in fast pace, communicate, problem solving, take ownership, think out-of-box and cross examine requirements.

Should be capable of working in multiple development projects(agile), answerable to mulitple stakholders , attend scrum meetings and do presentations.

Should have ability to learn new techniques, process and interact closely with clients.

Should posses good knowledge in different AWS services and ability to suggest techniques to the client(not architect level).

Interact with different teams, ability to debug and suggest process for the activity.

Some knowledge on advanced analytics, deployment of ml models and retraining strategies.