Roles and Responsibilities

• Build and maintain reusable Python modules for ML model performance evaluation and monitoring.


• Develop logic for generating executive summaries, insights, and recommendation outputs for model monitoring reports.


• Design and implement modular frameworks for automated report generation in PDF and dashboard formats.


• Standardize model monitoring templates including visualizations, commentary, KPI thresholds, and performance metrics.


• Develop automation and orchestration workflows to schedule recurring monitoring runs and archive outputs.


• Process and analyze large-scale model outputs using Databricks, PySpark, and parquet datasets.


• Collaborate with data scientists, ML engineers, and business stakeholders to enhance model governance and monitoring capabilities.