Etsy is a marketplace where people around the world connect, both online and offline, to make, sell and buy unique goods. Etsy is also a tech company that invests in the craft of coding and data-driven product development as a strategic priority. Etsy has employed AI and machine learning to tackle personalization, recommendations, image understanding, item similarity, search relevance, spelling correction, and many other tasks. We’ll talk through several examples of how Etsy leverages data, where it’s excelled, and where this hammer hasn’t quite hit the nail on the head.
We will be asking ourselves hard questions, recognizing the limitations of decisions driven purely by big data:
“A misanthrope who teetered on the edge of buffoonery but never quite fell in, an egotist blind to his own failings, a charming drunk; and a man who hated children, dogs, and women, unless they were the wrong sort of women.” | | Actually, that’s WC Fields, but, it’s pretty close to me, though a different gender. With an incessant need for knowing more facts. Basically I am WC Fields + Johnny 5 of Short Circuit.
Gio has been working with data, architecting systems, and leading teams of engineers for over a decade. At Etsy he’s a Staff Software Engineer leading the Search Ranking Team. He’s focused on Search from the ground up: infrastructure, ranking and machine-learned relevance, diversity, fairness, autosuggest, faceting, navigation, experimentation, etc. His work sits at the crossroads of a number of disciplines so he spends his days collaborating with infrastructure engineers, data scientists, analysts, product managers, user researchers, and taxonomists. Prior to working at Etsy, Gio worked at CapitalIQ where he designed, built, and maintained a multi-terabyte database, real-time processing-system, and search engine for globally-sourced financial reports.