Staff Data Scientist, Trust & Safety
Brief Info About Vinted
Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre-loved clothing and lifestyle items, giving each piece a second life – or even a third.
The Vinted Group is made up of three business units that support this mission:
Vinted Marketplace is Europe’s leading platform for second-hand fashion and a go-to destination for all kinds of pre-loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life.
Vinted Go enhances the shipping experience with a vast network of over 500,000 pick-up and drop-off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high-value pieces.
Vinted Pay is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members.
Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people.
Information About The Position
You'll join Vinted's Trust & Safety domain, whose mission is to protect the Vinted community from harmful activities and content. Across several detection, moderation and sanctioning teams, we run a growing set of machine learning models, rule engines, and LLM agents. They score every new listing, account and message at Vinted's scale, and many of them act on members automatically.
We're looking for a Staff Data Scientist to shape the architecture and effectiveness of our detection systems as a whole. You'll tackle problems that individual teams cannot solve independently: how to maximize detection coverage, combine different m...
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