Fnu Gitanjali

Designed scalable ingestion pipelines migrating 3,000+ Excel files into Snowflake and built a reusable star-schema with 12+ FACT tables to standardize KPIs, reducing manual handling by 90% and cut refresh latency from hours to minutes.

Optimized supply chain and logistics using SQL and Tableau to reduce logistics costs by 15% and excess stock by 10%, and built predictive models to forecast inventory needs and support data-driven decisions.

Built scalable ETL pipelines in Azure Data Factory and ADX, optimized DAX and DirectQuery to improve report speed by 35%, and processed build telemetry impacting 750M+ devices to enhance reporting and dashboarding.

Analyzed 1B+ records and built ETL pipelines with Airflow and Databricks Spark to process large-scale telemetry, improving ETL performance by 40% and increasing user engagement metrics via A/B testing and analytics.

Analyzed inbound call data with Excel and SQL to optimize staffing and SLAs, reducing call wait times by 9% and improving NPS by 5%, and built Redshift ingestion workflows to streamline analytics.

Grade: 3.8

Activities and societies: Teaching Assistant for Calculus for Business, Applied Machine Learning, Integral Calculus, Vectors & Matrices; relevant coursework in machine learning, deep learning, statistical methods, and time series forecasting.

Completed a Master of Science in Data Science with coursework and TA responsibilities in applied machine learning and calculus, graduating with a 3.8 GPA.

Completed a Bachelor of Engineering in Information Science and Engineering.