Rayon Hussain

Diagnosed and resolved ~60 data incidents monthly and processed 5–10TB monthly in GCP BigQuery; automated scalable pipelines that reduced manual operations by 40% and cut data inconsistencies by 25%.

Developed 3 interactive Tableau dashboards that accelerated month-end close by 25% and implemented data validation controls that reduced discrepancies by 98%, improving finance decision-making and regulatory reporting accuracy by 30%.

Built and maintained dashboards and reports in Looker and Google Sheets, improved data accuracy via Python/PostgreSQL integrations, and drove a 20% uplift in client insights and 12% increase in upsell rates.

Designed healthcare risk-assessment and employee engagement dashboards integrating CSV/SQL sources, improving identification of at-risk individuals and increasing actionable insights by 25% and forecasting accuracy by 15%.

Created interactive Tableau dashboards that improved FOIA compliance reporting, increasing data accuracy by 35%, boosting public service efficiency by 15%, and identifying $250K in annual savings.

Optimized Snowflake data models to boost query performance 20%, transitioned 50+ Cognos reports, and streamlined ETL with Azure Data Factory and Python to increase data delivery by 35% and reduce manual effort by 20%.

Grade: 3.7

Completed a Master of Science in Data Science with a 3.7 GPA focusing on applied data analysis, machine learning, and data engineering.

Earned a Bachelor of Technology in Computer Science with coursework in programming, data structures, and software engineering.