Business Intelligence Engineer at PayPal with a Masters Degree in Information Systems (Data Analysis). I am currently working at a place where we are revolutionizing how money is used throughout the globe. FinTech is a complex, fast paced industry and I am glad to be a part of it with one of the Industry leaders in the space.
- Design robust & scalable ETL solutions for Merchant Data which is used for PS Analytics & reporting purposes.
- Design, develop and implement a BI platform for reporting & analytics used by PS Management.
- Machine learning pipeline in python to predict Merchant Churn for PS.
- Used PayPal Notebooks (Jupyter) for ad-hoc modeling and analysis.
- Analyzing data with SQL and Python (Pandas)
- Written scheduled python scripts to move tables from Teradata to our PS reporting Data warehouse.
- Develop graphs/dashboards and schedules in Tableau.
- Development of reports, dashboards, interactive graphs, charts & maps in Tableau for end-users.
- Run ad-hoc data analysis on Teradata and MySQL Data warehouses to produce actionable insights.
- Normalization, flattening and cleansing activities performed on timely basis.
- Proficient in Google Analytics suite for user behavior metrics.
- Used Google Cloud instances to host/deploy applications in cloud.
- Salesforce CRM admin & development to migrate from OSC to Salesforce.
- Proficient in designing techniques like Snowflake schemas, Star schema, fact and dimension tables, logical and physical modeling.
- I have worked under the Oracle Business Unit of Capgemini Consulting, Mumbai (India). I have worked on Oracle PeopleSoft ERP 9.1 HCM module with PeopleTools 8.52. I have worked on offshore support project for a reputed European Client.
- I have been trained on various modules of PeopleSoft and also trained on PeopleSoft Campus Solutions, Oracle Taleo Recruiting.
- Duties involved development and enhancement of various PeopleSoft pages, components etc. with client communication and interaction on daily basis.
- As a part of my duty, I have prepared numerous reports for clients on daily basis using PSQuery, Oracle BI and SQR's.
- Automation of manual activities in this project being one of my major accomplishments.
- Database monitoring and server space monitoring were also part of my weekly activities.
- Troubleshooting and bug fixation was also a part of my job and we used BMC remedy tool for incident management.
ML Classifier Engine to predict ticket root causes - Currently engaged in building a ML classifier using NLP. Goal of the engine is to be able to predict the possible root cause (disposition) of a ticket. Algorithm learns from a training data-set of 12000 tickets across 16 causes, this is a classic Multi-Class classification problem that I am trying to solve.
Churn Prediction Model - Worked on building a Churn prediction model, which identifies the customers likely to Churn.