Applied Data Scientist
San Francisco, CA

Job Description

Yelp has hundreds of millions of pieces of user-contributed content, millions of users and business listings, and hundreds of thousands of advertising customers - and all of these numbers are constantly growing. Making sense of this data, deducing relationships between variables, and figuring out different interactions is hard work, but these insights are hugely impactful to Yelp's business. Applied data scientists uncover these insights through exploratory research and analysis, and carry the ideas all the way through to production-grade statistical or predictive models. They work in areas including pricing models and auction bidding strategies, learning to rank applications, personalized recommender systems, and causal inference.

This position is hiring into our Customer & Sales Intelligence team in London, which focuses on optimizing business-facing areas such as customer acquisition and retention, lifetime value estimation, and dynamic pricing.

Yelp engineering culture is driven by our values: we're a cooperative team that encourages individual authenticity and "unboring" 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.

What You Will Do:

* Conduct end-to-end analyses, from wrangling data via SQL/Spark/Python, to statistical modeling, to hypothesizing and presenting business ideas.
* Work with large, complex datasets.
* Lead the development of predictive and causal models.
* Productionize and automate model pipelines within Python services.

We Are Looking For:

* 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
* Motivation to develop deep product and business knowledge and to connect abstract modeling and analysis tasks with business value
* Comfort in using a Unix environment

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

At Yelp, we believe that diversity is an expression of all the unique characteristics that make us human: race, age, sexual orientation, gender identity, religion, disability, and education - and those are just a few. We recognize that diverse backgrounds and perspectives strengthen our teams and our product. The foundation of our diversity efforts are closely tied to our core values, which include "Playing Well With Others" and "Authenticity."

We're proud to be an equal opportunity employer and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition or disability.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, you may contact us at accommodations-recruiting@yelp.com or 415-969-8488.

Note: Yelp does not accept agency resumes. Please do not forward resumes to any recruiting alias or employee. Yelp is not responsible for any fees related to unsolicited resumes.