Manager, Member Experience - Ads Dse

Netflix Netflix · Big Tech · United States · Remote · Data & Insights

Manager for Netflix's Member Experience team within Ads Data Science and Engineering. This role focuses on understanding and optimizing the impact of ad delivery policies on member experience using causal inference and predictive models. The team will build models and workflows to drive ad delivery optimization, balancing revenue, member experience, and advertiser outcomes. The role involves leading a team of ML Scientists, Data Scientists, and Analytics Engineers, fostering partnerships, and ensuring high-quality technical outputs.

What you'd actually do

  1. Hire, inspire, and grow high-performing Machine Learning Scientists, Data Scientists, and Analytics Engineers.
  2. Lead strong partnerships with stakeholders from across the business - from product management, engineering, consumer insights, content, and strategy.
  3. Instill an inclusive culture that is innovative and collaborative, both within your team and in the broader organization.
  4. Develop a team charter and roadmap that optimizes the impact of the team and reflects evolving business needs.
  5. Act as an ambassador between the Product, Engineering, Strategy, and DSE teams by having a deep knowledge of how the Netflix Ads product works.

Skills

Required

  • Experience building and leading hybrid Data Science and ML teams in the Ads space.
  • Demonstrated tenacity, resilience, and leadership experience that enables you to organize and drive cross-functional projects, overcome challenges, and propose solutions.
  • Be both quantitative and qualitative.
  • player-coach
  • Superb communication skills
  • Capacity and passion to translate business objectives into actionable analyses, and use analytics to guide product and business with quantitative recommendations.

Nice to have

  • A passion for TV and movies and defining the future of entertainment.

What the JD emphasized

  • builds causal inference and predictive models
  • use them in ad delivery optimization
  • apply rigorous analytical methods to evaluate concepts, dissect challenges, build models and workflows

Other signals

  • builds causal inference and predictive models
  • use them in ad delivery optimization
  • apply rigorous analytical methods to evaluate concepts, dissect challenges, build models and workflows