
201 - 500 employees
Founded 2014
đź’Ľ Consulting
🏥 Healthcare
📦 Logistics
đź’° $200M Series D on 2021-08
Consulting • Healthcare • Logistics
LaunchDarkly is a software company offering a platform for feature management and experimentation. Its solutions allow developers to control software releases through feature flags, enabling safeguarded and progressive rollouts. The platform integrates with various developer tools and supports multiple programming languages to streamline deployment and improve the developer experience. LaunchDarkly's solutions cater to industries including financial services, healthcare, high tech, retail, and government, among others, providing a robust infrastructure that aids in delivering customized and targeted user experiences.
🔥 3 minutes ago
🇺🇸 United States – Remote
đź’µ $256k - $352k / year
⏰ Full Time
đź”´ Lead
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201 - 500 employees
Founded 2014
đź’Ľ Consulting
🏥 Healthcare
📦 Logistics
đź’° $200M Series D on 2021-08
Consulting • Healthcare • Logistics
LaunchDarkly is a software company offering a platform for feature management and experimentation. Its solutions allow developers to control software releases through feature flags, enabling safeguarded and progressive rollouts. The platform integrates with various developer tools and supports multiple programming languages to streamline deployment and improve the developer experience. LaunchDarkly's solutions cater to industries including financial services, healthcare, high tech, retail, and government, among others, providing a robust infrastructure that aids in delivering customized and targeted user experiences.
• Own the Experimentation pillar, including product strategy, roadmap delivery, commercial outcomes, and investment across experimentation, warehouse-native analysis, and scalable infrastructure. • Partner with AI product, observability, and core feature management leaders to make experimentation the measurement layer of the AI software development lifecycle. • Build a closed loop from offline evaluation through production experiments, automatic promotion and rollback, and self-improving feedback loops for agents. • Win sophisticated, high-maturity data-science buyers by defining and shipping statistical, warehouse, and experiment-workflow capabilities. • Expand warehouse-native coverage across major data warehouses and query layers. • Deliver analysis-only mode, variance reduction, ratio and percentile metrics, exposure validation, and arbitrary-window analysis. • Run a high-performing product function, manage quarterly roadmap commitments, drive AI-assisted engineering productivity, and hire where gaps exist. • Represent the product externally to data scientists, PMs, experimenters, analysts, and partners; translate strategy to the field and equip sales for competitive evaluations. • Deliver improved experimentation deal win rates, strategic reference customers, active-customer and ARR growth, experimentation attach rate, engineering throughput, and AI-assisted development adoption.
• Senior product leader at GM, VP, or equivalent level with a track record owning a product line competing on statistical rigor and data infrastructure. • Deep operator-level fluency in experimentation methodology, including causal inference, variance reduction, ratio metrics, sequential testing, exposure design, multi-armed bandits, and composite/multi-objective metrics. • Experience running experimentation at scale against production data warehouses and non-deterministic systems where output variance affects sample-size and significance decisions. • Credibility with data science leaders and experimentation specialists at sophisticated organizations, with the ability to recruit them. • Experience leading a function comprising engineering, design, and data science. • Ability to set multi-quarter roadmaps, champion investment allocation, and report results to executive teams and boards. • Clear, direct communication and fast decision-making with incomplete information. • Opinionated perspective on experimentation in an AI-native world, including how agents and autonomous systems use experimentation infrastructure. • Preferred: Built or scaled experimentation as core infrastructure. • Preferred: Personally won competitive evaluations where sophisticated data-science organizations were the deciding voice. • Preferred: Shipped warehouse-native data products and understands customer data-infrastructure operations.
• 20% Bonus • Restricted Stock Units (RSUs) • Health insurance • Vision insurance • Dental insurance • Mental health benefits
Apply Now🔥 2 hours ago
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