Business & Marketing Data Science Manager

Google Google · Big Tech · Seattle, WA +1

Manager for Data Science role focused on developing and deploying AI/GenAI algorithms for personalization, setting measurement strategies, leading data analysis, and driving business outcomes using OKRs. Requires experience in applying quantitative methods, developing statistical algorithms, establishing data pipelines, presenting ML outputs to stakeholders, and providing technical leadership for production-ready predictive models.

What you'd actually do

  1. Develop and deploy AI / GenAI algorithms and models to personalize platform capabilities for learners.
  2. Set the measurement strategy and oversee the creation of tools and dashboards to track solution deployment.
  3. Lead the analysis and interpretation of data, providing expert technical feedback to address analytical challenges.
  4. Direct the shift from tracking data to using OKRs to drive the right outcomes for the business; enabling best practices and data driven behaviors across CLS.
  5. Identify and lead the resolution of product gaps by analyzing user feedback and key metrics.

Skills

Required

  • AI/GenAI algorithm and model development
  • Personalization techniques
  • Measurement strategy development
  • Data analysis and interpretation
  • Statistical algorithms and optimization models
  • Data engineering pipelines
  • Dashboarding and data visualization
  • Machine learning model deployment
  • Stakeholder communication and translation of complex ML outputs
  • Technical leadership and architectural oversight
  • Mentoring data scientists
  • Cloud-based ML platforms

Nice to have

  • Experience in the learning business
  • Knowledge of OKRs
  • Experience with global marketing spend and operational strategy optimization

What the JD emphasized

  • Application of quantitative methods to unstructured business challenges and complex, multi-dimensional datasets
  • Development of statistical algorithms or optimization models and methods
  • Establishment of data engineering pipelines or dashboarding for data visualization
  • Leading the strategic interpretation and presentation of complex statistical and machine learning outputs to senior business stakeholders, translating results into actionable insights to optimize global marketing spend and operational strategy
  • Providing technical leadership and architectural oversight to a team of data scientists on the development, validation, and deployment of production-ready predictive models, including mentoring the team on best practices for coding, model versioning, and cloud-based ML platforms

Other signals

  • Develop and deploy AI / GenAI algorithms and models to personalize platform capabilities for learners
  • Set the measurement strategy and oversee the creation of tools and dashboards to track solution deployment
  • Lead the analysis and interpretation of data, providing expert technical feedback to address analytical challenges
  • Direct the shift from tracking data to using OKRs to drive the right outcomes for the business
  • Identify and lead the resolution of product gaps by analyzing user feedback and key metrics
  • Define team level OKRs and partner with Strategy & Operations and the leadership team around outcome driven measurements