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Head of Experimentation

LaunchDarkly· Product
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Remote$256k - $414kFull-timePosted 2mo ago

About the role

Leader responsible for owning the Experimentation pillar, driving AI-native experimentation capabilities, and positioning LaunchDarkly as the definitive experimentation platform in an AI-accelerated world.

Responsibilities

  • Own the Experimentation pillar. Direct leadership of the Product team. Partner with Engineering and Design counterparts in a triad model. Accountable for the pillar's strategy, roadmap delivery, and commercial outcomes. Make the investment case across in-product experimentation, warehouse-native analysis, and scalable infrastructure.
  • Make experimentation the measurement layer of the AI SDLC. Partner with AI product, observability, and core feature management leaders to productize AI-native primitives. Build a closed loop from offline evaluation through production experiments, to automatic promotion/rollback, to a self-improving feedback loop for agents.
  • Win the high-maturity buyer. Earn the technical confidence of senior data scientists and data-focused PMs. Decide non-negotiable capabilities and ship them on a timeline that wins pivotal reference deals.
  • Make warehouse-native a weapon. Expand coverage across major data warehouses and query layers. Deliver parity on analysis-only mode, variance reduction, ratio and percentile metrics, exposure validation, and arbitrary-window analysis.
  • Operate a high-performing function. Run a disciplined roadmap, ship predictably against quarterly commitments, drive AI-assisted engineering productivity, and hire where gaps exist.
  • Be the external face of the category. Represent the product with Data scientists, PMs, experimenters, analysts, and partners. Translate strategy to the field and equip sales to win head-to-head.

Qualifications

  • Senior product leader (GM, VP, or equivalent) with a track record of owning a product line that competes on statistical rigor and data infrastructure.
  • Deep fluency in experimentation methodology: causal inference, variance reduction, ratio metrics, sequential testing, exposure design, multi-armed bandits, and composite/multi-objective metrics; experience running at scale with production data warehouses and non-deterministic systems.
  • Earned credibility with data science leaders and experimentation specialists at sophisticated organizations; ability to recruit them.
  • Led a function including engineering, design, and data science; comfortable multi-quarter roadmap planning, investment allocation, and reporting to execs and board.
  • Clear, direct communicator. Decides fast with incomplete information. Prefers shipping and learning over exhaustive docs.
  • Opinionated about AI-native experimentation and how agents/autonomous systems will use experimentation infrastructure differently.

Skills

Required:Experimentation methodologyLeadership and cross-functional alignmentCommunication and storytelling

Benefits

  • RSUs, health, vision, and dental insurance, and mental health benefits in addition to salary.
Last updated Aug 12, 2026. Interested? Apply on the company site.
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