Lead Product Manager - Ads Auction and Measurement
@ Yelp

Hybrid
$194,000
Hybrid
Full Time
Posted 1 day ago

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XXXXXXXXX XXXXXXXXX XXXXXXX****** @yelp.com
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Job Details

Overview

Yelp engineering culture is driven by our values: authenticity, creativity, and collaboration. Yelp connects people with local businesses through reviews and an advertising platform that powers millions of connections daily.

About the Role

As the Lead Product Manager - Ads Auction and Measurement, you will own the product strategy for Yelp's core ad auction system. You will drive the development of auction, bidding, pricing, and pacing mechanisms through close partnership with engineering and data science teams.

What You Will Do

  • Define and drive the roadmap for ads auction systems.
  • Collaborate on algorithm & system optimization with technical teams.
  • Develop robust metrics and run large-scale A/B tests.
  • Conduct independent data analysis using SQL and Python.
  • Lead cross-functional teams to enhance business impact.

Requirements & Experience

  • 5+ years of technical product management experience.
  • Expertise in auction theory, optimization, and statistical modeling.
  • Strong data analysis skills with SQL and Python.
  • Advanced degree in a quantitative field is highly preferred.
  • Excellent communication and collaboration skills.

What You'll Get

Competitive compensation ranging from $155,000 to $233,000 annually along with bonus, restricted stock units, and robust benefits. This is a fully remote opportunity available across Canada.

Key skills/competency

  • Product Management
  • Ads Auction
  • Measurement
  • Auction Theory
  • Optimization
  • Data Analysis
  • SQL
  • Python
  • A/B Testing
  • Cross-functional Leadership

How to Get Hired at Yelp

🎯 Tips for Getting Hired

  • Research Yelp's culture: Learn about values and engineering practices.
  • Customize your resume: Highlight auction and analytics experience.
  • Align with role: Emphasize product strategy and technical fluency.
  • Prepare for interviews: Review case studies and data challenges.

📝 Interview Preparation Advice

Technical Preparation

Review auction theory fundamentals and algorithms.
Practice SQL queries on large datasets.
Brush up on Python for data analysis.
Study A/B testing and statistical methodology.

Behavioral Questions

Describe a challenging cross-team project.
Explain your approach to complex problem solving.
Discuss handling feedback and team disagreements.
Share how you manage multiple priorities.

Frequently Asked Questions