Requirements
- Writes modular, testable Python and SQL code for data science workflows, model development and maintenance.
- Applies core machine learning techniques with a focus on time series forecasting.
- Trains and deploys machine learning models using Docker on cloud platforms such as Azure ML.
- Prepares and transforms data for modeling using scalable, code-first pipelines (e.g., Databricks, dbt).
- Applies Git-based version control and CI/CD pipelines to automate data workflows.
- Is self-driven and takes initiative to move tasks and projects forward independently.
- Works effectively in agile teams, collaborating across data engineering, governance, and business stakeholders.
