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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
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