• Built and fully automated the refreshing of dashboards for business teams - eliminating manual calculations that were done on the weekly basis.• Improved ETL pipeline for dashboards through SQL code-refactoring.• Recommended new segmentation methods to more effectively detect fraudulent transactions coming in through classification techniques.

• Creating, enhancing and maintaining of functional ESG‑related Tableau Dashboards to convey key business insights for business use cases.• Data wrangling using Python and Excel through ad‑hoc data analytics requests raised by business teams.• Conducted extensive research work on novel ESG‑related metrics and concepts to provide clarity for team. • Managing and Revamping of the ETL pipeline (in SQL Snowflake) for live Tableau dashboards used by the business team. • Cleaning of ETL pipeline to improve dashboard performances.

• Built and deployed traditional Machine Learning (ML) models (SVM, Random Forest, Logistic Regression and Time Series) as well as Neural Networks (Keras).• Provided predictive analytics support using Time Series forecasting for sales of their products to understand which products may/may not do well in the coming months.

• Worked with Adobe Analytics and Metabase (SQL) to study trends to better understand consumers’ purchasing behaviour/site navigation behaviour, to minimise churn rate.• Built Machine Learning models in Python (Natural Language Processing ‑ Sentiment Analysis) to draw insights from textual feedback on consumers’ attitudes towards Circles.Life