Machine Learning for Product Managers
With Paul Sheets and Rahul Srivastava
Machine Learning Project Readiness with Paul Sheets
Readiness to begin the modeling process from a business perspective – has the team checked off all the things needed to ensure success, along with an emphasis on how the iterative and experimental nature of a Data Science / Machine Learning project is different than a typical software development project. The goal would be to help managers avoid common mistakes in this space that can result in a model being dead on arrival, which is an extreme waste of an organizations resources, and can be a major reason that Data Scientists quit.
The Role of Product Management in a Machine Learning Project with Rahul Srivastava
How is the role of product manager different in different stages of a Machine Learning project? Once the model is ready, what does it mean to take a model into production? Rahul will talk about pitfalls and opportunities when it comes to data collection, success definition alignment, and ways to measure the impact of your project.
6 - 6:30 Networking (Food & Beverages)
6:30 - 8 Talk
About the Speakers
Paul Sheets is the Director of Data, Machine Learning Engineering & Data Science at zulily. Paul has been with zulily for 2 ½ years. Prior to zulily, Paul led the Data Science team for Starbucks’ Loyalty Program. He is a lifelong learner, with a career spanning Software Engineering, Business Intelligence / Data Warehousing, and Predictive Analytics. He enjoys bringing coding skills, business acumen, and math together to help leaders make better business decisions. A former instructor and Northwest Chapter President at The Data Warehousing Institute, his research interests include high-performance and parallel computing, machine learning, ensemble methods, automated feature selection, and reproducible research. He holds an M.S. in Software Systems Engineering from George Mason University and a B.S. in Information System Management from UMBC.
Rahul Srivastava is the Manager of Product Management - Big Data and Machine Learning at zuliliy. Rahul manages zulily’s product team for Big Data and ML. He has been with zulily for 4 years and has owned product features around personalization, customer engagement, and marketing tech. Prior to zulily, Rahul was at Amazon where he worked on expanding Amazon Fresh from Seattle to SF and LA. He also launched on Same day delivery, Prime Fresh, and 1-click recipe ingredient purchase. Rahul has a MBA in corporate finance from University of Maryland and a MS in Comp Sci from University of Stony Brook. Besides sending him time on ramping up on Big Data and ML, Rahul is learning how to make craft cocktails.