We will share our experiences in building Data Science and Machine Learning (DS/ML) into organizations. As new DS/ML teams are created, many wrestle with questions such as: How can we most efficiently achieve short-term goals while planning for scale and production long-term? How should DS/ML be incorporated into a company?
We will bring unique perspectives: one as a previous Databricks customer leading a DS team, one as the second ML engineer at Databricks, and both as current Solutions Architects guiding customers through their DS/ML journeys.We will cover best practices through the crawl-walk-run journey of DS/ML: how to immediately become more productive with an initial team, how to scale and move towards production when needed, and how to integrate effectively with the broader organization.
This talk is meant for technical leaders who are building new DS/ML teams or helping to spread DS/ML practices across their organizations. Technology discussion will focus on Databricks, but the lessons apply to any tech platforms in this space.
Joseph Bradley works as a Sr. Solutions Architect at Databricks, specializing in Machine Learning, and is an Apache Spark committer and PMC member. Previously, he was a Staff Software Engineer at Data...
Chris joined Databricks in July of 2019 as a Solutions Architect. Previously, as Director of Data Science for Digital Marketing and Fraud Prevention at Overstock, he and his team utilized big data and...