Roles & Responsibilities : Tracking and Reporting processes covering KPIs, including deliverables and project / program updates, budget, and risks / mitigations for use by the CEO and other governance bodies.
Understanding of Supervised and Unsupervised ML paradigms
Exposure to Core Frameworks (Tensorflow, Caffe, PyTorch, SparkMLlib, etc.)
Exposure AI ML Platform Services including AutoML (AWS Sagemaker, AutoPilot)
Technology :
Languages and Packages : SQL, Python, Conda Package Manager, R, R*Shiny, scikit-learn, Spark, JavaScript.
Cloud Services : AWS (Sagemaker, Lake Formation, S3, EC2, etc.), Google Cloud, Azure Services, AWS Services S3, AWS SageMaker
Databases : MySQL, MS SQL, Oracle, Neo4J
Data Automation : Lake Formation, Palantir Foundry, Spark
Data Analytics Tools : Power BI, Palantir Foundry, HubSpot, Google Analytics
Tools and Environments : JIRA, Bitbucket, Confluence, Palantir Foundry, Jupyter Notebook, MLFlow