Todd is a Sr Solution Architect at CarMax responsible for Data Science and ML platforms and has been working on defining and standing up the DS/ML platforms to truly enabled their Business Data Scientists in with richer, larger, and traditional data. Key is to drive incremental growth for all of CarMax’s key business units.
April 23, 2019 05:00 PM PT
CarMax, a member of the Fortune 500 and the S&P 500, and on the Fortune 100 Best Companies to Work For® list for 14 consecutive years, is the nation’s largest retailer of used vehicles. A key initiative for CarMax is enabling their data scientists and analysts to leverage machine learning and their massive volumes of sales, clickstream and other data to drive an omni-channel experience with a goal of creating a personalized customer experience online and anywhere.
To achieve this, CarMax adopted Apache Spark and Azure Databricks to unify their data science and engineering teams so they can harness machine learning to power their recommender, batch, and real-time algorithms which are key to creating a better customer experience. The solution enables their Data Engineering teams to access and ingest massive volumes of data to feed into their ETL pipeline feeding into their data lake while providing their Data Science teams with interactive workspaces to be more productive working on their models at scale.
In this talk, CarMax will share their journey to creating an omni-channel experience for their millions of customers, the data and analytics architecture that enables their teams to process and model large volumes of batch and real-time data, lessons learned along the way, and some of the models and algorithms they use to create a highly-tailored customer experience spanning the online and brick-and-mortar world