Los Angeles Metropolitan Area
Business Intelligence Engineer & Applied Statistician with 6+ years of experience engineering scalable data systems, automating production ETL pipelines, and deploying AI-driven workflows. Proven track record at Amazon and AT&T of bridging the gap between complex data infrastructure and high-level business strategy to optimize live operations and decision making.
· Designing, building, and maintaining a production sales and inventory reporting schema · Implementing AI solutions to automate manual loading of inventory and sales reports · Creating and managing Python Jobs and SQL ETLs to process data from external vendors · Managing logical item breakdowns and mappings, item and sales channel categorization, and ensuring compliance with designated standards and database policies
Create automated reporting using Tableau and Power BI and build automated data flows using Palantir, Vertica, and Snowflake systems. Develop reporting to explain predictive forecasting and track performance against real outcomes. Designed and built a proof-of-concept reporting web portal to help organize and centralize reports across multiple teams integrating multiple Tableau and Power BI servers.
Managed a SQL Reporting Services Server by publishing reports, assigning security roles, creating subscriptions, and building data sets for analysts to build reports off. Designed database schemas and ETL flows in a SOX compliant database to create a reporting data structure and assisted analysts with the development of SQL Queries needed to create their reports. Built automated processes to audit data quality.
Uses predictive modeling to forecast inventory changes and customer demand. Works with Project Managers to monitor progress on software migrations effecting 300+ employees. Develops and maintains an Interactive Voice Response system that handles 10,000+ calls per day and allows customers to make payments, check balances, and find property information over the phone. Design database schemas and create ETL process to blend data from multiple sources for reporting.
Maintained and contributed to a revenue management system that analyzed global market conditions to make pricing recommendations based on current and predicted future demand. Tuned decision and learning algorithms, implemented business rules, and ran back-cast simulations on different learning algorithms to see how they would have performed in previous years. Researched improvements to pricing strategies, promotional offers, and handling of foreign currency.
Built and maintained predictive models to identify high value guests and optimize contact timelines. Developed procedures to meaningfully segment audiences for personalized advertising. Worked with a production database to create automated reporting tools and optimized SQL reporting.