Master of Science in Data Science (STEM Designated)

Bachelor of Technology in Information Technology

IT Analytics - Data Scientist Intern

• Developed a customer segmentation model to categorize customers based on RFM (Recency, Frequency, Monetary) technique in Azure Databricks using PySpark to improve marketing decisions for business and sales team.
• Implemented a Time Series Forecasting Model using Seasonal Auto-Regressive Integrated Moving Average (SARIMA) to forecast the product units to be sold to avoid additional manufacturing and inventory costs.
• Developed a Product Recommendation model using Apriori Algorithm to recommend products to the customers based on their past purchasing pattern.
• Worked on a proof of concept to migrate data from SAP HANA to Azure platform to analyze its efficiency; built automated ETL pipelines thus reducing time and saving manual work using PySpark, SQL, Azure Databricks and Azure Data Factory.
• Developed data pipelines to ingest, transform data from various resources using Spark, SQL, Python and created dashboards to visualize the insights using Microsoft Power BI.

Software Engineer

• Developed a supervised model using python to identify the high-risk tickets which helped analysts to pay more attention to the cases generated based on specific alerts with an accuracy of about 82%.
• Created scheduler jobs for Actimize visual modeler and Autosys file watcher using Shell Scripting to reduce dependency with middleware and Production Assurance team.
• Played a key role in setting up a cloud-based environment to migrate all our existing applications to AWS cloud that reduced the operation cost of handling the multiple internal servers by 35%.
• Cleansed, transformed, and analyzed unstructured AML (Anti-Money Laundering) data and created an interactive dashboard using Tableau to visualize the hidden fraudulent cases that helped analysts to take preventive measures earlier.