Product Solutions and Operations Manager, Google Play Store

Google Google · Big Tech · Mountain View, CA +2

This role focuses on managing and scaling solutions that leverage human insights and machine learning for the Google Play Store. The primary responsibility involves designing, running, and owning human computation tasks to produce reliable labeled data, which feeds into systems for app recommendations and training/evaluating ML models. The role also involves collaborating with product and engineering teams to launch new features, improve data quality, and explore LLM-first solutions.

What you'd actually do

  1. Own product data streams, partnering with subject matter experts to implement evaluations to production and collect data from rater teams at scale.
  2. Collaborate with Product Management, Engineering and Product Marketing teams to launch new products, scale operations, surface critical data signals to increase user engagement and improve developer Return on Investment (ROI).
  3. Track data quality and operational Key Performance Indicators (KPIs) and perform analysis to drive continuous improvement and troubleshoot issues.
  4. Work closely with global vendor raters, vendor managers and vendor trainers to identify gaps or issues in data collection, and design and implement solutions to address them.
  5. Stay up to date on the latest data labeling methods, including human rater labeling and machine learning, and make recommendations for LLM-first solutions to scale output.

Skills

Required

  • Bachelor's degree or equivalent practical experience
  • 5 years of experience in a technical project management or a customer-facing role
  • 3 years of experience managing projects from inception to completion within a global organization
  • 3 years of experience in human computation or data labeling

Nice to have

  • Experience working with product and engineering teams
  • Experience in designing, implementing and managing product development and operationalization frameworks and methodologies
  • Experience with prompt engineering and human computation
  • Ability to make smart tradeoffs and rapidly launch and iterate new product features for a user-facing commercial organization
  • Excellent problem solving skills, with the ability to analyze research or performance data, develop insights and apply them to optimize the product roadmap

What the JD emphasized

  • human computation
  • data labeling
  • evaluations
  • data quality

Other signals

  • human computation
  • data labeling
  • machine learning models
  • evaluations
  • LLM-first solutions