Alejandro Cantarero, Ph.D.

Data, Technology, Engineering, Product

I've spent the last several years building data products and solutions at different companies in the Los Angeles area from seed stage start-ups to large enterprises.

My experience includes building out multiple data teams at different companies, consolidating existing data elements inside a company, setting up a culture for success, and a proven track record of delivering data products that drive value for the organization.

Current Position

VP Data, Los Angeles Times

Rebuilding the Digital Marketing and Data organizations at the Los Angeles Times after its sale by the Tribune Publishing Company

Upcoming and Recent Events

Marketing Analytics and Data Science 2019 - San Francisco, CA - April 10th, 2019

Creating a data team as well as a platform on which to build solutions to deliver to your business is a challenge. Even when you successfully complete this first part, and now you have all the data and machine learning at your fingertips, deploying those solutions into a legacy marketing team presents a host of other challenges. Join us to hear lessons learned in how to effectively integrate technology, build teams and deliver insights

SimplyData - Santa Monica, CA - November 29th, 2018

Title: Building a successful data organization


When building a data team from scratch or inheriting an existing team, there are plenty of questions to ask when thinking about how to successfully deliver on our mission to the company. Should data engineering be part of the data organization or does it sit better with the engineering team? Data scientist is a job title that means a lot of different things to different companies, what does it mean to us? Are we aligned around platforms or functions? What's our strategy around data governance and compliance? And that's just to name a few.

This talk will present some insights from prior experience on structuring data teams, both at startups and larger legacy organizations, covering examples that have been both successful and not so successful, and lessons learned in each case.