Building machine learning systems with high predictive accuracy is inherently hard, and embedding these systems into great product experiences is doubly so. To build truly great machine learning products that reach millions of users, organizations need to marry great data science expertise, with strong attention to user experience, design thinking, and a deep consideration for the impacts of your prediction on users and stakeholders. So how do you do that?
Today’s guest is Sam Stone, Director of Product Management, Pricing & Data at Opendoor, a real-estate technology company that leverages machine learning to streamline the home buying and selling process. Sam played an integral part in developing AI/ML products related to home pricing including the Opendoor Valuation Model (OVM), market liquidity forecasting, portfolio optimization, and resale decision tooling. Prior to Opendoor, he was a co-founder and product manager at Ansaro, a SaaS startup using data science and machine learning to help companies improve hiring decisions. Sam holds degrees in Math and International Relations from Stanford and an MBA from Harvard.
Throughout the episode, we spoke about his principles for great ML product design, how to think about data collection for these types of products, how to package outputs from a model within a slick user interface, what interpretability means in the eyes of customers, how to be proactive about monitoring failure points, and much more.
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#222 [Radar Recap] Scaling Data Quality in the Age of Generative AI
#221 [Radar Recap] The Future of Programming: Accelerating Coding Workflows with LLMs
#220 [Radar Recap] Building Tomorrow's Workforce, Today: Scaling Internal AI Academies
#219 Building a Data Platform that Drives Value with Shuang Li, Group Product Manager at Box
#218 Designing AI Applications with Robb Wilson, Co-Founder & CEO at Onereach.ai
#217 Data & AI at Tesco with Venkat Raghavan, Director of Analytics and Science at Tesco
#216 Perplexity & the Future of AI with Denis Yarats, Co-Founder and CTO at Perplexity AI
#215 Seeing the Data Layer Through Spatial Computing with Cathy Hackl and Irena Cronin
#214 Learning & Memory, For Brains & AI, with Kim Stachenfeld, Senior Research Scientist at Google DeepMind
#213 Building Trust Through Data with Prukalpa Sankar, Co-Founder of Atlan
#212 The History of Data and AI, and Where It's Headed with Cristina Alaimo, Assistant Professor at Luiss Guido Carli University
#211 What is AIOps? With Assaf Resnick, Co-Founder & CEO of BigPanda
#210 Trust and Regulation in AI with Bruce Schneier, Internationally Renowned Security Technologist
#209 Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at Away
#208 Monetizing Data & AI with Vin Vashishta, Founder & AI Advisor at V Squared, & Tiffany Perkins-Munn, MD & Head of Data & Analytics at JPMC
#207 Data Driven Venture Capital with Andre Retterath, Partner at Earlybird VC
#206 The Venture Mindset with Ilya Strebulaev, Economist & Professor at Stanford Graduate School of Business
#205 The 2nd Wave of Generative AI with Sailesh Ramakrishnan & Madhu Iyer, Managing Partners at Rocketship.vc
#204 Data & AI Trends in 2024, with Tom Tunguz, General Partner at Theory Ventures
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