As an applied scientist within the Ads group, you will be joining a team that focuses on pricing and auction bidding strategies, control systems, and experimentation. Applied scientists uncover these insights through exploratory research and analysis, and carry the ideas all the way through to production-grade statistical or predictive models. Making sense of this data, thinking deeply about system design, and figuring out different network interactions is hard work, but these insights are hugely impactful to Yelp’s business.
This opportunity is fully remote and does not require you to be located in any particular state within the US. We welcome applicants from throughout the US. 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.
What you'll do:
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:
A Bachelor’s Degree or an equivalent work experience is required.
A degree in a quantitative discipline such as Computer Science, Statistics, Econometrics, Applied Math, Physics, etc.
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 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 applied 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:
Compensation range is $106,000-235,000 annually. You may also be offered a bonus, restricted stock units, and benefits.
This opportunity has the option to be fully remote in all locations across the US.