Backed by 2 years of professional experience, I specialize in turning raw data into strategic clarity - blending statistical rigor with product-driven analysis to build reliable, insight-driven solutions!
+ Translating data signals into product recommendations using quantitative models, opportunity sizing, sensitivity analysis, and scenario modeling.
+ Decision-intelligence pipelines built on Bayesian modeling, hypothesis testing, uplift modeling, and confidence-driven guardrails.
+ Automating EDA, reporting, QC checks, and data refresh workflows using Python, Pandas, Airflow, dbt, git and AWS or other cloud-based CI/CD.
+ Outcome-driven narratives translating complex telemetry into product, GTM, and strategy-defining insights for leadership.
+ Distributed data engineering patterns: streaming ingestion, event-driven processing, delta Lakehouse optimization, and metadata governance.
+ Cloud-native deployments across AWS, GCP, Snowflake, and Oracle Analytics with infra-as-code, containerized compute, and serverless ETL.
+ Built & scaled data pipelines integrating MongoDB, Firebase, Adjust, Feather, AWS & GCP, enabling 150+ product issue deep-dives with rapid turnaround.
+ Automated analytics using Python, SQL & BI tools, boosting KPI visibility across teams and reducing decision time by 40%.
+ Performed advanced player lifecycle analytics—cohort, funnel, segmentation—improving retention (+18%), engagement (+22%), and monetization (+15%).
+ Optimized ad performance across Meta & GCP, improving acquisition ROI by 25%.
+ Led VIP revival strategy using data-driven segmentation, re-engaging 108 VIP users with $34K LTV recovery.
+ Delivered end-end data engineering + analytics solutions for global clients.
+ Built automated ETL pipelines using Python, SQL, AWS, C#, F#, improving data quality & real-time reporting.
+ Developed dashboards & machine learning insights enabling clients to improve operational efficiency & decision-making.
+ Performed statistical modeling & validation using Python & SQL, increasing data accuracy by 40%.
+ Identified performance opportunities that improved conversion efficiency by 22%.
+ Built automated pipelines improving reporting efficiency 3X and reducing manual work by 50%.
+ Delivered real-time analytical insights using Python, improving leadership decision speed.
Built a fully automated CI/CD pipeline on AWS (EC2, S3, CodeBuild, CodeDeploy, CodeArtifact) enabling seamless builds, versioning, and zero-downtime Java app deployments. Standardized releases, removed manual effort, and established a cloud-native DevOps deployment backbone.
View Details →Developed Streamlit, Python, C#, and Spark-based analytical applications combining real-time computation with dynamic dashboards. Delivered predictive insights and automated intelligence layers that accelerated decision-making across stakeholders.
View Details →10+ End-to-End ML Projects spanning predictive modeling, classification, optimization algorithms, statistical analysis, and data engineering workflows.
View Details →Built a real-time metadata engineering workflow using Python and YouTube/Spotify APIs to extract, cleanse, and map track-level data, enabling automated cross-platform playlist synchronization and insight generation.
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