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Applied Scientist

Yelp · Apr 1st 2021

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As an Applied Scientist on Trust & Safety you will employ your analytical skills to detect and understand content spam at Yelp. You will set up robust statistical experiments to characterize user behaviour, assess our models through careful statistical analysis, and 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 and creative solutions to problems. We enable all new team members to deploy working code their first week, and your impact will only grow from there with the support of your manager, mentor, and team. At the end of the day, we’re all about helping our users, growing as engineers and scientists, and 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.

Where You Come In:

  • Must be based or willing to relocate to the UK

  • Identify and own challenging problems, form testable hypotheses, and drive significant business impact

  • Lead the design and analysis of experiments or development of causal and predictive models to test your ideas

  • Collaborate with product and engineering to affect changes in production systems and provide intelligence to other teams

  • Communicate your conclusions to technical and non-technical audiences alike

  • Keep the team and our projects current on new developments in ML and statistics by reading papers and attending conferences and local events

  • Productionize and automate model pipelines within Python services

What it Takes to Succeed:

  • Based or willing to relocate within the United Kingdom

  • Experience with data analysis/statistical software and packages (pandas/statsmodels/sklearn within Python, R, etc.)

  • Experience with predictive modeling/machine learning, forecasting, or causal inference

  • A degree in a quantitative discipline such as Computer Science, Statistics, Econometrics, Applied Math, etc.

  • A love for writing beautiful code; you don’t need to be an expert, but experience is a plus and we’ll expect you to learn on the job

  • A demonstrated capability for original research, the curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal

  • The motivation to develop deep product and business knowledge and to connect abstract modeling and analysis tasks with business value

  • Comfortable working in a Unix environment

What You'll Get:

  • Full responsibility for projects from day one, an awesome team, and a dynamic work environment

  • Competitive salary with equity in the company, a pension scheme, and an optional employee stock purchase program

  • 25 days paid holiday initially, rising to 29 with service

  • Private health insurance, including dental and vision

  • Flexible working hours and meeting-free Wednesdays

  • Regular 3-day Hackathons and weekly learning groups, always with interesting topics

  • £58 per month toward any exercise of your choice

  • Quarterly offsites

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