Slate Planning Manager, Games

Netflix Netflix · Big Tech · United States · Remote · Netflix Games Studio

Netflix is seeking a Slate Planning Manager for its Games division to oversee portfolio-level strategy for game discovery and promotion. This role involves data-informed decision-making, cross-functional coordination with various Games teams, and optimizing the allocation of promotional resources to maximize game installs and engagement. The manager will help establish processes and guardrails, analyze performance, and influence stakeholders to ensure a portfolio-first approach.

What you'd actually do

  1. Support the portfolio-level slate strategy for how Netflix Games titles are prioritized across launches, live service beats, and evergreen programming in an always-on environment.
  2. Develop clear, data-backed recommendations on how to allocate limited placements and visibility to maximize installs, gameplay, and long-term value.
  3. Act as a central coordination point for slate and placement needs across multiple Games GMs and studio stakeholders.
  4. Gather and synthesize inputs from Gaming Vertical GMs, Product, and other partners into clear, structured proposals for portfolio visibility.
  5. Collaborate with Data Science & Engineering and Games Title Product Management to analyze performance and improve the targeting, effectiveness, and efficiency of Games placements.

Skills

Required

  • 5-8 years of experience in digital merchandising, platform programming, editorial strategy, or portfolio planning
  • Demonstrated ability to contribute to portfolio-level decisions, including tradeoffs in constrained environments
  • Strong data fluency, comfortable using quantitative and qualitative insights to shape recommendations and support stakeholder discussions
  • Experience working cross-functionally with senior partners who own P&Ls or product verticals
  • Excellent judgment, structured thinking, and the ability to clearly explain why certain opportunities should be prioritized over others

Nice to have

  • Passion for games, discovery, and building scalable systems that improve outcomes over time

What the JD emphasized

  • portfolio-level strategy
  • data-backed recommendations
  • allocate limited placements and visibility
  • identify and surface potential collisions
  • gather and synthesize inputs
  • highlight tradeoffs
  • establish and maintain processes, frameworks, and guardrails
  • analyze performance and improve the targeting, effectiveness, and efficiency
  • use data, experimentation, and insights
  • track performance across placements and surface learnings
  • inform and influence stakeholders’ decisions
  • communicate recommendations and tradeoffs
  • reinforce a portfolio-first mindset