Duncan Mc Crae
About
Duncan works in the following industries: "Computer Software", and "Internet". In Duncan's previous role as a Product Manager, Timeline Ranking at Twitter, Duncan worked in until Aug 2021. Prior to joining Twitter, Duncan was a Product Manager, Internationalization at Twitter and held the position of Product Manager, Internationalization at San Francisco Bay Area. Prior to that, Duncan was a Co-Founder at Presto (Acquired), based in Philadelphia, PA from Aug 2017 to Aug 2018. Duncan started working as 3rd Party Merchant (Independent) at Amazon in Corte Madera, CA in Apr 2012.
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Duncan Mc Crae's past jobs
Product Manager on Twitter's recommendation and ranking team. We build the machine learning personalization systems that power the ranked timeline, notifications, and discovery products.
Product lead for the Internationalization team. Our goal is to ensure anyone, anywhere can fully participate in the public conversation on Twitter. Launched "Auto-Translate", a product that automatically translates all foreign language Tweets in users’ timelines. Shipped a new model to infer user language which lead to a 150k+ increase in DAU. Developed and implemented metrics to measure machine translation quality. Product proposal presented to the CEO is now used as an exemplar proposal for all Twitter PMs.
Acquired Summer 2018 by Medallia-Zingle. Deployed in thousands of hotels including Hyatt, Four Seasons, and Marriott properties. Presto developed predictive NLP models that perform classification, similarity analysis, and entity recognition in the hospitality domain. We set out to improve the quality and efficiency of text-based guest interactions in hotels. Presto's mission is to create experiences better than humanly possible. I built Presto with my brother from our dorms rooms at the University of Pennsylvania and UC Berkeley.
Built a six-figure revenue amazon storefront while in high school. 100% self-run, Bootstrapped from $0, initially drop shipping first products. Developed a method to track pricing and sales across thousands of products on Amazon. Used this data to identify underserved products to sell on the Amazon Marketplace.