Role overview
- Build and maintain reusable Python functions for calculating stand model performance metrics – develop
And maintain the logic for generating executive summaries and recommendations.
- Design and implement a modular framework to generate monitoring reports in PDFs or dashboard formats.
- Standardize templates for model reporting including visualizations, commentary sections and KPI thresholds.
- Build automation scripts using orchestration to schedule monitoring runs at regular intervals and integrate
with the storage system for output archival.
Salary : 100000-115000/per annum
What we're looking for
- 7-10 hands-on experience Python with expertise in pandas, NumPy, scikit-learn, matplotlib and seaborn.
- Strong understanding of ML evaluation metrics across classification and regression use cases.
- Experience with Databricks Notebooks and PySpark for handling large model outputs in parquet format.
- Experience in working with PDF generation libraries.
- Knowledge of MLFLow, model registries or production ML monitoring platforms.
Tags & focus areas
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