Manager, Data Science & Engineering - Title & Launch Management

Netflix Netflix · Big Tech · United States +2 · Remote · Data & Insights

Manager for a Data Science and Engineering team at Netflix, focusing on building automated systems and AI/agentic solutions for content launch and promotion. The role involves leading a multidisciplinary team, shaping strategy, and driving execution of end-to-end AI solutions.

What you'd actually do

  1. Oversee a diverse portfolio of end-to-end efforts to design, deploy, and rigorously evaluate autonomous AI solutions, advancing Netflix’s title launch strategy and supporting our rapidly expanding slate of content.
  2. Coach, empower, and elevate a team of analytics engineers, data scientists, and machine learning practitioners, increasing their impact and supporting their career development.
  3. Collaborate with a cross-functional team to shape the vision and roadmap for the area, prioritize and drive execution.
  4. Define and cultivate a high standard for both velocity and technical excellence, while nurturing a culture grounded in strong engineering and scientific rigor.
  5. Leverage advanced technical skills and deep product and domain insight to surface new problem spaces and make bold, high-conviction decisions.

Skills

Required

  • Proven track record of successfully leading data and ML-focused teams
  • Deep expertise in autonomous agentic systems and applied ML
  • Demonstrated commitment to staying current on the latest research
  • Led teams that launch and iterate on production ML services
  • Mentoring and developing talent
  • Recruiting and growing researchers and engineers
  • Master’s or PhD in Machine Learning, Computer Science, or a closely related field
  • 6+ years of hands-on ML experience (or 4+ years with a relevant PhD)
  • 2+ years of experience leading ML teams
  • Exceptional verbal and written communication skills
  • Ability to influence and align diverse stakeholders
  • Deep commitment to driving end-to-end business impact

Nice to have

  • Experience with advanced analytics
  • Experience with AI/agentic solutions
  • Experience with content ingestion and distribution systems

What the JD emphasized

  • autonomous AI solutions
  • agentic systems
  • applied ML
  • production ML services
  • leading data and ML-focused teams
  • rigorous measurement
  • agentic/AI-driven solutions
  • autonomous agentic systems
  • applied ML
  • production ML services
  • leading teams that launch and iterate on production ML services
  • end-to-end business impact, not just building models

Other signals

  • AI/agentic solutions
  • autonomous AI solutions
  • agentic systems
  • applied ML
  • production ML services