Will Chiong
About
Will Chiong is from New York, New York, United States. Will works in the following industries: "Information Services". Will is currently Principal Software Engineer at Earnest Research, located in New York, New York, United States. In Will's previous role as a Senior Backend Engineer at Bayesian Health, Will worked in Remote until Feb 2021. Prior to joining Bayesian Health, Will was a Senior Data Engineer at Spotify and held the position of Senior Data Engineer at New York, NY. Prior to that, Will was a Staff Software Engineer at Patreon, based in New York, NY from Apr 2018 to Sep 2019. Will started working as Technical Co-Founder at Kit.com in New York, NY in Mar 2015. From Sep 2011 to Mar 2015, Will was Lead Software Engineer at Gilt.com, based in New York, NY. Prior to that, Will was a Vice President at Morgan Stanley, based in New York, NY from Aug 2002 to Sep 2011. Will started working as Research Assistant at Columbia University in Jan 2001.
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Will Chiong's current jobs
Will Chiong's past jobs
Kit acquired by Patreon Worked on integrating Kit's product domain knowledge into a full-service Merch product for Patreon creators to automatically patron-loyalty based merchandise to their members.
Kit is a social platform and product graph that enables our users to make helpful product recommendations to their friends and followers. Highlights: ● We've built a simple, intuitive, fast, and beautiful interface to enable the creation of "kits" of the products you recommend for any activity or profession. ● Your kit will be optimized for presentation in search engine result pages and when shared on social networks and platforms. ● We make it easy to share your kit on blogs or websites including SquareSpace, Medium, Wordpress, and other popular providers. ● Kit automatically composes beautiful images and animated gifs to represent your kits, combining images from various internet sources, as well as user-uploaded content. Images are optimized to be shared on all major social networks and platforms. ● We have integrated with retailers to provide opportunities for creators to make money on their recommendations. ● We have a robust and scalable user search experience that makes it easy for users to find the best product recommendations for any activity.
Technical Lead for Personalization and Recommendation Algorithms. Managed a team developing algorithms for matching users with relevant sales and recommending products to individual users based on their inferred and explicit preferences. Built predictive models for analyzing customer behavior to optimize the personalized customer experience across all channels. Customized an ETL process to combine and transform multiple sources of customer behavioral data into a unified stream of datapoints that could be used to power performant realtime personalization experiences.
Lead developer for a project to develop and leverage a conceptual model relating pricing, reference, and firm data content. Lead developer for a suite of Java web-based data access, normalization, and distribution services and architect for firm access strategies.
Worked in the Graphics and UI Lab. Designed and implemented an SDK for thin-client distributed computing using JFC and RMI. Results submitted to ACM conferences for publication published at Eleventh Annual World Wide Web Conference in 2002.