Note: The job is a remote job and is open to candidates in USA. LaunchDarkly is a company focused on improving software delivery and helping developers innovate faster. As a Staff Engineer on the Experimentation team, you will build a platform for data-driven decision-making, design statistical engines, and lead adaptive experimentation efforts.

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

Skills

• 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

Benefits

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

Company Overview

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