Who is Jun Yu? Overview
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Quick answer
Jun Yu is listed as Buyer Growth at Whatnot, based in Greater Seattle Area, United States. AeroLeads shows a work email signal at snap.com and a matched LinkedIn profile for Jun Yu.
Jun Yu previously worked as Senior Engineering Manager (ML & Growth) at Snap Inc. and Adjunct Professor at University Of Washington - Michael G. Foster School Of Business. Jun Yu holds Doctor Of Philosophy (Phd), Machine Learning, Computer Science from Oregon State University.
Company email context
Email format at Whatnot
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{first}@snap.com
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Profile bio
About Jun Yu
* Have 10+ YoE working in Growth. Being a single-threaded owner of key growth products, launching 0-to-1 products, and improving existing ones to drive user growth in both social (Snapchat) and e-commerce platforms (Amazon, eBay).* Have 15+ YoE building large-scale Machine Learning and recommendation systems used by hundreds of millions of users daily such as friend recommendation, search, push notification and email targeting, SEM, and risk management.* Have strong technical leadership with a track record of setting clear visions for the team, building and scaling high output teams, coaching engineers and growing leaders, effective communication with executives, and fostering a culture of ownership, candor, innovation, and craftsmanship.
Listed skills include Machine Learning, Scalding, R, Data Mining, and 31 others.
Current workplace
Jun Yu's current company
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8 roles
Jun Yu work experience
A career timeline built from the work history available for this profile.
Senior Engineering Manager (Ml & Growth)
CurrentI support the Friending product team, the Growth Machine Learning team, the Growth Foundation & Data team, and the Graph Understanding Platform at Snap. We develop features to help users make virtuous friends on Snapchat, deliver ML solutions and infrastructure to power growth products (e.g., friend recommendations, push notification, search, in App send-to, and off-platform sharing), and build the Graph Understanding Platform to mine signals from complex entity relationships on Snapchat, unlocking new business opportunities. My team is looking for kind, smart and creative engineers (client, cackend, infra, and machine learning). Please drop me a note if you are interested.
Oct 2019 - Present
Adjunct Professor
I have a passion in teaching and helping more people into the field of machine learning and data science. Currently I teach several machine learning courses in the Foster School of Business at University of Washington, including advanced ML (MSIS 522), Deep Learning and Big Data (MSIS 549), and NLP (MSIS 541).
Sep 2018 - Feb 2024
Senior Applied Scientist / Tech Lead
I led several machine learning driven projects including: 1) seller personalization and recommendation on seller central homepage, 2) seller email governance and suppression, 3) seller downstream impact analytics, and 4) sourcing best quality products for Amazon promotions.
Oct 2017 - Oct 2019
Staff Applied Researcher / Tech Lead In Marketing Science
Our team uses machine learning techniques to power eBay Paid Internet Marketing, including search (Google, Bing), social (Facebook), and display. - Optimize the bids of keywords (Text Ads) and eBay listings (Product Listing Ads) sent to Google and Bing so that we improve the ROI and brings more new buyers to eBay. - Design bidding strategies to retarget eBay users via social and display.- Content recommendation in retargeting.Tech stack: Scalding, Spark, Scala, Python and R.Award: eBay Critical Talent Award and eBay Seattle Technical Achievement Award.
Aug 2015 - Oct 2017
Senior Applied Researcher In Trust Science
In eBay Trust Science team, I built large-scale machine learning models to manage seller risk and reduce defects (bad buyer experience) on eBay via Search Ranking, Merchandizing, and Marketing. Our production job processes Terabytes of data daily on Hadoop to predict the risk of 30+ million active sellers and has banked over 100+ million dollars GMB lift over the next 12 months. I have been recognized for this work and won the eBay Spot Award.
Dec 2013 - Aug 2015
Graduate Research Assistant
PhD Dissertation - Species Distribution Modeling using Citizen Science DataSpecies distribution modeling (SDM) is to predict the species range spatially. We develop a probabilistic graphical model that incorporates the expertise of observers to build SDMs using data from a large-scale citizen science project.Data quality control in citizen science projects: Data quality is essential for SDM in citizen science projects. We build up an automated data verification process for eBird project and show that it identifies 50\% more invalid observations and reduces the human screening efforts by about 40\% compared to the expert-defined data filters.Discovering species confusions: One way to improve the skills of novice birders is to teach them how to distinguish confusing species. We propose to discover observer confusion between species by modeling multiple species simultaneously and show that this information helps novice birders contribute better quality data.Multi-species distribution modeling: Single-species model can not capture species interactions is SDM. To address this problem, we apply a multi-label learning algorithm on this problem and show that multi-species modeling improves the predictions, especially on the rare species.
Sep 2006 - Dec 2013
Ph.D. Intern @ Search Science
Inexperienced users with different purchase intents use ambiguous queries. We propose a Latent Dirichlet Allocation-based approach to retrieve diverse items so that the risk of users with diverse intents not seeing any relevant items is minimized. Our LDA-based approach improves the user satisfaction at eBay by more than 6\% compared to the eBay production ranker.
Jun 2012 - Sep 2012
2 education records
Jun Yu education
Doctor Of Philosophy (Phd), Machine Learning, Computer Science
Oregon State University
Bachelor Of Science, Computer Science
Wuhan University
FAQ
Frequently asked questions about Jun Yu
Quick answers generated from the profile data available on this page.
What company does Jun Yu work for?
Jun Yu works for Whatnot.
What is Jun Yu's role at Whatnot?
Jun Yu is listed as Buyer Growth at Whatnot.
What is Jun Yu's email address?
AeroLeads has found 1 work email signal at @snap.com for Jun Yu at Whatnot.
Where is Jun Yu based?
Jun Yu is based in Greater Seattle Area, United States while working with Whatnot.
What companies has Jun Yu worked for?
Jun Yu has worked for Whatnot, Snap Inc., University Of Washington - Michael G. Foster School Of Business, Amazon, and Ebay.
How can I contact Jun Yu?
You can use AeroLeads to view verified contact signals for Jun Yu at Whatnot, including work email, phone, and LinkedIn data when available.
What schools did Jun Yu attend?
Jun Yu holds Doctor Of Philosophy (Phd), Machine Learning, Computer Science from Oregon State University.
What skills is Jun Yu known for?
Jun Yu is listed with skills including Machine Learning, Scalding, R, Data Mining, Matlab, Algorithms, Java, and C++.
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