Are you intrigued by data? Yelp has hundreds of millions of pieces of user-contributed content, millions of users, & millions of business listings - & all of these numbers are constantly growing. Making sense of this data, deducing relationships between variables & figuring out different interactions is challenging work, & these insights are hugely impactful to Yelp's core business.
Yelp is trusted by our users, every day, to help make decisions about where to eat, which mover to call, or best places to visit in a new city. Our team's mission is to surface high-quality content that reflects authentic experiences generated by real Yelpers who are engaged with the community. Join a team of experts on opinion & content spam & get the chance to contribute to the growth of one of the leading companies in this problem space.
As an Applied Scientist on Trust & Safety you will employ your analytical skills to detect & understand content spam at Yelp. You will set up robust statistical experiments to characterize user behaviour, assess our models through careful statistical analysis, & build end-to-end machine learned models that impact hundreds of millions of consumer contributions.
Yelp engineering culture is driven by our values: we're a cooperative team that encourages individual authenticity & creative solutions to problems. We enable all new team members to deploy working code their first week, & your impact will only grow from there with the support of your manager, mentor, & team. At the end of the day, we're all about helping our users, growing as engineers & scientists, & having fun in a collaborative environment.
We'd love to have you apply, even if you don't feel you meet every single requirement in this posting. At Yelp, we're looking for great people, not just those who simply check off all the boxes.