Spearheaded the setup of core processes and best practices for the Trust Data Science team, including data governance, reliability improvements, and foundational dataset development.

Developed a real-time Metrics Dashboard by building a Flink-based streaming service to process live event data and generate platform health metrics, significantly improving incident response.

Led a org-wide initiative to overhaul data logging practices, enabling self-serve access to key metrics and reducing dependency on the DS team.

Built and maintained a central warehouse that powers foundational datasets, ensuring high data quality and freshness within defined SLAs for 50+ Tier1/Tier2 datasets.

Designed a scalable analytics query gateway service for the Customer Obsession domain at Uber, enabling flexible metric querying across multiple data sources and reduced onboarding time.

Led a data governance project to enhance data management practices by establishing clear ownership for datasets and implementing Time to Live (TTL) policies.

Developed real-time Audience Size Estimation which reduced processing time from 2 hours to 5 minutes with a small error margin.

Co-developed an ETL pipeline in Apache Spark for Rule-based Campaigns to improve efficiency for larger scales.

Co-developed the engineering pipeline to use machine learning model for campaigns which impacted revenue by 10 Million dollars.

Developed an application which analyzes log messages and alerts when an application goes down.

Improved the existing algorithm by 3 times and disk space by 20 times.

Implemented clustering and graph algorithm techniques to find Human Traffickers and reported to DARPA.

Signature based approach and PageRank approaches worked better.

Developed front-end of web application to manage APIs.

API Service Providers can track metrics like response time, API traffic and add restrictions like API calls/user using smartGWT.

Developed sales dashboard which shows all the analytics of what products are selling fast with different filters like category, location and time-wise.