Anurag Das

About Anurag Das

I am a solution-driven professional with over 7 years of robust experience in data analysis, stakeholder management, and leading high-performing teams. I am a Senior Business Intelligence Engineer dedicated to transforming complex data into actionable insights that propel operational excellence and revenue growth. My technical proficiency spans SQL (advanced), Python, Tableau, Power BI, and additional tools such as Google Sheets, Microsoft Office, Google Data Analytics, and Adobe Analytics.At the core of my professional journey is a history of significant contributions to major projects at renowned firms like Amazon and Uber India. My efforts have led to a 13% increase in package delivery efficiency and a remarkable $5M rise in monthly bookings through strategic optimization of airport taxi campaigns. These achievements stem from my expertise in deploying complex data analytics techniques, including cohort analysis, A/B testing, and predictive forecasting models, which I leverage to craft powerful, decision-driving dashboards and reduce operational costs.As a leader, I have guided diverse teams of analysts to unearth and harness insights that enable pivotal business decisions, particularly in mobility and marketing verticals. My ability to blend advanced analytics with acute business understanding allows me to enhance campaign effectiveness and customer retention strategies, ensuring substantial business impact.Currently, I am enriching my skills through a Product Management Program, aiming to refine my capabilities in overseeing innovative, data-driven solutions to tackle intricate business challenges. My goal is to continue leveraging my analytical prowess to deliver data solutions and strategic business value at the intersection of technology and industry needs.

Experience

1. Business Intelligence Engineer Ii

   Amazon

   Aug 2024 — Present · Hyderabad, IN

   Stops Optimization:o Developed and implemented new logic for Repeat UC/OC MGRS grids, resulting in a 25% year-over-year decrease in Egregious MGRS, aligning with Stops TLT goals. Introduced a novel measure to calculate the percentage of MGRS grids with service time outliers, improving repeat service time estimation accuracy.o Designed and launched the Stops MGRS P0 Dashboard, identifying egregious MGRS with recurring delivery issues. Enhanced existing Stops MBR dashboard with MGRS page 0 view and conducted RSR analysis to pinpoint defective RSR MGRS grids. Dashboard features include under-consolidation, over-consolidation, and service time underestimation pattern detection.Workload Management:o Spearheaded the development of a Centralized HIVE dashboard, consolidating critical operational hotspots across Workload, Stops, and RSQ dimensions. Implemented weekly ranking of top 50 defective MGRS 100m grids, enabling focused improvement efforts.o Optimized the Workload P0 metrics dashboard, significantly reducing manual effort required for MBR metrics compilation and analysis.o Enhanced the Splits Attribution dashboard with new backtracking and EMB metrics. Implemented functionality to differentiate effects on split vs. non-split routes and track MBC-split rate relationships, providing deeper insights into route efficiency.

Education

• Indian School of Business

  Product Management Program, Product Management

• Jadavpur University

  Bachelor of Engineering - BE, Computer Science and Engineering