About The Position

Google Shopping is a comprehensive product search engine, a fast-growing product ads business, and an everyday essentials marketplace. We aim to revolutionize shopping by building great user experiences that bring users, retailers, and manufacturers together. The Consumer Shopping Data Science team works on Shopping products on various surfaces including .com, AI Mode, and Gemini. We are a shopping feature data science (DS) team within the Consumer Shopping DS, focused on building and evaluating AI-driven shopping experiences in Search (e.g., AI mode, AI Overview, etc.). As a Senior Data Scientist, you will lead analytics and measurement for key shopping features, working closely with Product and Engineering to shape development, experimentation strategy, and long-term roadmap decisions. You will play a critical role in defining how we build and measure user experience within emerging AI-powered features, delivering insights that directly influence product evolution. By applying advanced experimentation and analysis, you will drive data-informed decisions across our AI-driven shopping surfaces.

Requirements

  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years of work experience with a Master's degree.

Nice To Haves

  • Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
  • Experience with Gen AI Evaluation Science, ML and modern AI.
  • Experience working with peers and more executive stakeholders.
  • Ability to manage a product quality flywheel to inform iterations in model and product development.

Responsibilities

  • Lead analysis to shape the direction of AI-powered shopping features in Search and AI mode, including areas such as brand profile, user generated content and next-generation shopping experiences.
  • Design and analyze A/B experiments to evaluate shopping feature impact and tradeoffs.
  • Develop and operationalize novel measurement methodologies to quantify user behavior, engagement, quality, long-term user value for evolving shopping features.
  • Conduct post-launch and longitudinal analyses to understand the long-term impact, identify growth opportunities, and inform future product development.
  • Partner closely with Product, Engineering and User Experience (UX) to translate ambiguous product questions into clear frameworks and actionable insights.
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