Product Solutions and Operations Manager, Google Play Store

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

This role focuses on managing and scaling solutions for the Google Play Store, utilizing human insights and machine learning. The core responsibilities involve designing and owning human computation tasks for data labeling, collaborating with cross-functional teams to launch features, and ensuring the quality and reliability of data streams that feed into ML models and product decisions. The role emphasizes data quality, operational improvements, and staying updated on data labeling methods, including LLM-first solutions.

What you'd actually do

  1. 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 ROI.
  2. Own product data streams, partnering with subject matter experts to implement evaluations to production and collect data from rater teams at scale.
  3. Track data quality and operational 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.
  • 8 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.
  • Strong analytical skills and 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 streams
  • human rater labeling
  • machine learning