Close to 20 years measuring whether things worked. Now she builds them.

You've probably heard an AI project "saved hours." Few people can show you the before number. Raquel spent close to 20 years in analytics, including roles as Manager of Digital Analytics and Senior Manager of Analytics. The job was proving whether something worked before anyone celebrated.

At an eCommerce company, she governed GA4 tracking and QA through a migration. She wrote and validated SQL in BigQuery. She built Tableau dashboards that executives used as one source of truth. She agreed KPI definitions with leadership and ran recurring data office hours, so people could get answers without filing a ticket. In that role, she built a Tableau self-serve reporting platform that cut ad hoc report requests by 40%. She also automated weekly reporting workflows, cutting manual effort by 60%.

At a marketing technology company, she was the analytics lead between enterprise clients and a data science team. She scoped machine learning use cases and pulled and shaped data in SQL. She improved attribution by matching orphaned sales records to customer IDs. She also worked on predictive modeling for email subject lines.

That's why every AI build here starts with a baseline and ends with a 30-day review. The measuring habit came first.

She has hands-on AI training through Anthropic, Microsoft, DeepLearning.AI, and Udemy. She also builds and runs AI workflows for her own businesses. One is an automated LinkedIn publishing workflow: it drafts posts, renders images, sends her a review email, and schedules the approved posts. Another is a Notion operating system tied to Claude. She runs her own print-on-demand online shop, so the ecommerce side isn't theory either.

Long Island, New York. She works remotely with firms anywhere in the US.