Technical owner of data systems relating to discovery, product recommendations, search optimization, product collection generators, and product quality inference.

I was responsible for the architecture, implementation, and maintenance of a production-scale data system with 300MM+ daily user events at Encortex. My expertise allowed me to efficiently manage the ingestion, transformation, summarization, integration, enrichment, and performance of large datasets. I oversaw the migration of BI analytics in order to increase analytics velocity and uncover insights across the organization, and provided engineering-certified data products to leverage data assets into revenue lifts. My efforts resulted in improved analytics performance, increased discoverability, and a real-time user targeting application based on analytics insights about user behavior. Additionally, I published in-depth analytics whitepapers that outlined action plans for the organization.

I ran the Internal Revenue Operations team as a Project Owner. This team is responsible for growing daily internal revenue to $20k+, managing business research related to email marketing channels across incubating verticals, and providing a stable platform for new venture market opportunities.

My role also rapidly expanded into people management within Analytics, where I was able to help grow my direct reports' careers and technical development.

The RevOps team runs on a data infrastructure foundation that I architected in early 2019, providing a set of UX abstractions to focus the team's work on the most important problems to be solved. This system provided a flexible configuration language for allocating distributed platform, data, and computational resources relevant to the optimization of marketing campaigns and research.

My technical contributions were designed by working directly with data analysts to architect robust software that balances the importance of fast turnaround on problems in Analytics against the quality of scalability, maintainability, and operability that are critical to a dependable software system.

Explored and manipulated large consumer datasets to uncover actionable insights, while developing, operating, and maintaining internal systems responsible for turning those insights into revenue.