Abhishek Maurya

About Abhishek Maurya

Strategic Data Leader with over 12 years of experience (6+ at Amazon) specialized in the dual pillars of Scalable Data Architecture and Product Data Science, bridging the gap between high-throughput engineering and rigorous causal analysis.• Expert in architecting petabyte-scale Data Lakehouses using AWS (S3, Redshift, Glue), optimizing data latency by 25% and enabling real-time diagnostic reporting for global-scale business units.• Proven track record in Product Growth, leveraging a proprietary \"At-Risk\" propensity model to drive a 20% lift in Day-30 retention for Prime Video through targeted Marketplace credit incentives.• Senior Experimentation Architect who has led A/B/n testing for cohorts of 30M+ customers, utilizing Causal Inference (Diff-in-Diff) to isolate incremental lift and pivot global marketing strategies based on behavioral \"intent decay.\"• Advanced Analytics Engineer proficient in dimensional modeling (Star/Snowflake schemas) and ETL/ELT orchestration via Airflow, reducing ad-hoc data requests by 40% through robust self-service frameworks.• Specialist in Predictive Modeling and Inference, deploying XGBoost, SHAP explainability, and Multi-Armed Bandits to optimize real-time content recommendations and drive multi-million dollar revenue gains.• Pioneer in AI-augmented Business Intelligence, architecting LLM-driven reporting layers (Amazon Bedrock) that automate complex narrative insights for executive-level Weekly Business Reviews (WBR).• Dedicated Technical Mentor and leader, having directed global teams of analysts to standardize North Star metrics and KPI definitions, ensuring data integrity and alignment across C-suite leadership.

Experience

1. Senior Business Intelligence Engineer

   Amazon

   Jun 2022 — Present · Seattle, WA, US

   Spearheaded the architecture of a scalable Data Lakehouse using AWS S3 and Redshift Spectrum, ingesting over 1TB of daily streaming data. • Developed a Generative AI-driven reporting layer that automated executive summaries, providing instantaneous insights for VPs. • Architected an automated onboarding journey for new Prime members; leveraged an \"At-Risk\" propensity model to trigger $6 Marketplace credits, driving TVOD adoption and improving 60-day Prime retention (Settled Starts)• Led a large-scale A/B experiment on \"Anticipation Support\" timing; identified a 30-day \"intent decay\" where a 13x lift in trailer views failed to drive incremental launch-week streaming, leading to a global shift toward 10-day \"continuous pulse\" marketing strategies• Engineered a churn propensity model using XGBoost and SHAP values to identify high-risk segments; collaborated with Product teams to deploy automated win-back triggers that achieved a 20% lift in Day-30 retention• Developed a Content Valuation Framework for a $15M portfolio using Causal Inference (Diff-in-Diff) to isolate the impact of 3rd-party titles on High-Value Action (HVA) acquisition, optimizing long-term ROI for contract renewals

Education

• GALGOTIA S COLLEGE OF ENGINEERING AND TECHNOLOGY, GREATER NOIDA

  Bachelor of Technology (B.Tech.), Electrical and Electronics Engineering

  2009 — 2013

• W. P. Carey School of Business – Arizona State University

  MS Business Analytics, Data Mining, Python, R, Marketing Analytics, Applied Analytics,

  2018 — 2019