Staff Engineer – Experimentation Team

🕒 Abril 16

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $182.600 - $295.350 / ano

⏰ Tempo Integral

🔴 Especialista

🧑‍💻 Engenheiro Full-stack

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LaunchDarkly

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2014

☁️ SaaS

🏢 Corporativo

💰 $200.000.000 Series D em 2021-08

SaaS • Enterprise

LaunchDarkly é uma empresa de software que oferece uma plataforma para gerenciamento de recursos e experimentação. Suas soluções permitem que os desenvolvedores controlem lançamentos de software através de feature flags, possibilitando implantações seguras e progressivas. A plataforma integra-se com várias ferramentas de desenvolvimento e suporta múltiplas linguagens de programação para simplificar a implantação e melhorar a experiência do desenvolvedor. As soluções da LaunchDarkly atendem a indústrias como serviços financeiros, saúde, alta tecnologia, varejo e governo, entre outras, proporcionando uma infraestrutura robusta que auxilia na entrega de experiências de usuário personalizadas e direcionadas.

Descrição

• Build the experimentation statistical engine — hypothesis testing, sequential analysis, variance reduction (CUPED, Winsorization), power analysis. Ensure statistical correctness across all experiment types. • Design warehouse-native experimentation that runs analysis inside customer warehouses (Snowflake, Databricks, Redshift, BigQuery). Build modular, warehouse-agnostic abstractions for rapid new backend support. • Lead adaptive experimentation — contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests. • Drive the platform roadmap with product, design, and data science. Shape what we build, not just how. • Collaborate cross-functionally with Warehouse Integrations, SDK, Platform, and Data Science teams. • Mentor engineers and raise the team's bar for statistical rigor and system design. • Own operational excellence — monitoring, observability, incident response, on-call. Robust telemetry and alerting.

🎯 Requisitos

• 10+ years building large-scale experimentation platforms, statistical analysis systems, or data-intensive backend services. • Applied-statistics knowledge: hypothesis testing, sequential analysis, variance reduction (CUPED), power analysis, experiment design. Comfortable with frequentist vs. Bayesian trade-offs. • Experience with adaptive experimentation ML — contextual bandits, Thompson sampling, Bayesian optimization, or RL-based allocation. • Track record designing warehouse-agnostic systems across Snowflake, Databricks, Redshift, BigQuery, or similar. • Expertise in Go, Python, or similar for backend services and statistical computation. • Experience with event-driven architectures, data pipelines, and large-scale data processing. • Cloud environments (AWS, GCP) with infrastructure-as-code. • Technical leadership: setting direction, breaking down complex problems, influencing across teams. • Ability to translate statistical concepts for product and engineering audiences.

🏖️ Benefícios

• Restricted Stock Units (RSUs) • Health, vision, and dental insurance • Mental health benefits