Pavan Wale

• Enhanced Data Modelling and decisioning(Upsell) - Predicting whether customer will be interested in buying different plans with in same product using AWS cloud Infrastructure. Technologies used for providing solution are AWS S3 Bucket, Sagemaker, Glue, lambda, step function, python(GBM) and pyspark.
• Broadband analytics - predicting the potential customer whose broadband connection would be affected by rainfall in next one year in order to help open reach business to invest on insulation. Technologies/methods used for providing solution are Granger causality test, Logistic regression, python, pyspark and hive.
• Python open-source repo manager for Data Scientist - A market place to securely download the required python open source packages for development and deployment of data science solution. Technologies involved are R-shiny, Shell scripting for backend.
• AI Data factory - A market place template registry to request GCP resources/service creation such as AI notebook instance, GKE cluster, SQL managed instance, GCS bucket, Kubeflow pipeline in private VPC network. Technologies involved Terraform, yaml, Gitlab runner setup in private docker containers.
• Personal learning project: Building TFX components using kubeflow orchestration and GCS bucket for artifact storage, SQL instance for metadata storage and cloud build for building container image and pushing it to container registry.

• Recommendation for Health industry - Recommending exercise to client for next 3 months and also predicting the time for which they need to perform to overcome the problems. Technologies involved R, PCA, K-means and KNN.
• Target Marketing and cross selling in plumbing and drain service industry - Predicting the customer churn and if he/she is not churning then classifying that customer to one of the revenue codes.
• Part time Data science lab instructor on technologies such as R, Python, HDFS, pySpark, hive and unix

Building custom dashboard on survey data for understanding the competency in telecom industry, Technologies involved are SQL, Excel and Tableau

Database and Unix administrator in the test and pre-prod environment. Technologies involved are Unix, shell scripting, Oracle SQL server and SQL.