Data Scientist 5 - Tv & Interactive Discovery

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

Data Scientist role focused on TV domain product innovation at Netflix, leveraging data science, experimentation, and emerging technologies like GenAI to improve member discovery experience. The role involves shaping product strategy, developing measurement frameworks, and influencing decisions through trustworthy outputs, with a focus on AI-assisted analytical workflows.

What you'd actually do

  1. Drive product innovation through robust measurement across experimentation, modeling, and analytics, with an overall product vision in mind
  2. Apply a member-centric lens to identify pain points and uncover how different member cohorts engage with product interventions
  3. Shape early investments in leveraging emerging technologies (e.g., GenAI) to improve the member discovery experience
  4. Establish strong partnerships with stakeholders to shape the vision of the space, whether that is by helping determine a product strategy or defining new metrics
  5. Develop experimentation and measurement frameworks to increase the velocity of investments and aid complex decision-making

Skills

Required

  • Ability to synthesize complex data into clear recommendations and influence product decisions across technical and non-technical audiences
  • Exceptional thought partnership and judgment, with the ability to build trusted relationships and independently drive ambiguous, high-impact problem spaces
  • Strong statistical intuition and experience applying experimentation and product analytics to consumer-facing product challenges
  • Strong technical fluency across SQL, statistical programming, and modern AI-assisted analytical workflows
  • Curiosity and adaptability in a rapidly evolving AI landscape, with a willingness to leverage emerging tools and workflows to accelerate learning, prototyping, and insight generation
  • Good judgment in balancing rapid stakeholder needs with scalable, reusable solutions that improve long-term leverage for the organization

Nice to have

  • Experience with algorithms as a product (e.g., recommendation systems, ranking algorithms)

What the JD emphasized

  • emerging technologies (e.g., GenAI)
  • AI-assisted analytical workflows
  • emerging tools and workflows

Other signals

  • Leverage AI-assisted workflows to innovate on how we learn via experimentation
  • Curiosity and adaptability in a rapidly evolving AI landscape, with a willingness to leverage emerging tools and workflows to accelerate learning, prototyping, and insight generation
  • Experience with algorithms as a product (e.g., recommendation systems, ranking algorithms) is a bonus