Applied Scientist - Ad Targeting

Applied Scientist - Ad Targeting

This job is no longer open
Do you want to help local businesses grow? Our Ad Targeting team connects millions of users to the right businesses each day. From restaurants, boutiques, and salons, to dentists, mechanics, and plumbers, our recommendation system knows just the place.

As an Applied Scientist, you will design robust A/B experiments to characterize user behavior, assess machine learning models through careful statistical analysis, and build end-to-end machine learning models that help millions of users make better decisions.

Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. We enable all new team members to deploy working code in their first week, and your impact will only grow from there with the support of your manager, mentor, and team. Learn more about Yelp by visiting: Culture at Yelp / Yelp Fact Sheet / Diversity at Yelp / Yelp Engineering Blog / Yelp Blog / Yelp Open Source / Yelp Economic Average.

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.

This opportunity is fully remote and does not require you to be located in any particular area in Canada. We welcome applicants from throughout Canada.

Where You Come In:

    • Identify and own challenging problems, form testable hypotheses, and drive significant business impact
    • Conduct end-to-end analyses, from wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
    • Communicate your conclusions to technical and non-technical audiences alike.
    • Develop and deploy ML models into production and continuously improve their performance.
    • Keep the team and our projects current on new developments in ML and statistics by reading papers and attending conferences and local events

What It Takes to Succeed:

    • 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.
    • Experience with machine learning packages such as xgboost, TensorFlow, etc. is a plus.
    • 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.

What You’ll Get:

    • This opportunity has the option to be fully remote in all locations across Canada.
    • For more information about Canadian benefits at Yelp, please check out this link.
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, disability, or any other protected status.

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.
This job is no longer open
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