* Predict client response rate for financial bank loans data

* Evaluates the responder percentage of clients when offered a loan, insurance , credit / debit card, etc. These offerings are classified under 8 tiers.

* Prepared the dataset using custom database schema.

* Ingest and load data from multiple data streams using Hadoop, Hive, Spark.

* Transformed the data and ingest data across ML pipelines for Data preprocessing

* Research, explore machine learning classification models

* Demonstrate the prediction reports using Shap, profiler, classification reports.

* Deployed the model script on Airflow.

* Custom Database schema design : Identifiedprojects falling under a domain, project closing deadlines ( dates).

* Data ingestion alerts: Load data, alert team about ETL failures, DAG failures, Py script server errors.

* Design custom dashboard for senior management to checkout projects that have completed , delayed , in-progress, closed, emergency targets.

* Test the individual power features and upgrade the model after multiple client and team reviews.

* The code was deployed later onto web by other interns in the team.