Purpose: Bridge data processing and model experimentation.
Key Responsibilities:
- Prepare, clean, and transform training datasets
- Perform EDA and feature engineering
- Support model experimentation and evaluation
- Build and maintain data pipelines
- Ensure data quality, consistency, and governance
Key Skills:
- Python, SQL
- Data processing tools (Pandas, Spark)
- Basic ML understanding
- Data pipeline tools (Airflow, etc.)
- Strong analytical thinking
