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Staff Engineer, Experimentation

LaunchDarkly· Core Engineering
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Remote$182.6k - $295.4kFull-timePosted 6mo ago

About the role

Staff Engineer on LaunchDarkly's Experimentation team building a platform for data-driven decision making through A/B testing, statistical engines, and warehouse-native analysis integrated with a feature management platform.

Responsibilities

  • 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.

Qualifications

  • 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.

Skills

Required:Hypothesis testingSequential analysisVariance reduction (CUPED, Winsorization)Power analysisContextual banditsBayesian optimizationGo, PythonWarehousing platformsEvent-driven architecturesCloud IaC

Benefits

  • RSUs
  • health, vision, and dental insurance, and mental health benefits in addition to salary
Last updated Aug 19, 2026. Interested? Apply on the company site.
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