Staff Engineer - Experimentation Team

About the role

As a Staff Engineer on LaunchDarkly's Experimentation team, you'll build the platform that helps engineering teams make data-driven decisions with confidence. Our Experimentation product enables customers to run A/B tests, measure the impact of feature changes, and optimize experiences - integrated with a feature management platform that processes trillions of evaluations daily. This role sits at the intersection of data science and platform engineering. You'll design the statistical engine, warehouse-native analysis pipelines, and adaptive experimentation systems (including contextual bandits) that power our customers' most important decisions. We want someone who brings genuine depth in applied statistics and ML - as fluent in statistical validity as in system architecture. You'll also architect warehouse-agnostic features that run analysis directly inside customers' data warehouses (Snowflake, Databricks, Redshift, BigQuery) - modular computation layers that abstract across warehouse environments while maintaining statistical correctness. Deep technical experience, a scientific mindset, and the ability to influence product and technical direction are critical. You'll lead by example: setting the bar for rigor, mentoring teammates, and owning systems end to end, including on-call.

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.

Requirements

• 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.
• Pay:
• Target pay ranges based on Geographic Zones* for Level 5:
• Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $214,800 - $295,350*
• Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $193,400 - $265,870**
• Zone 3: All other US locations - $182,600 - $251,0202**
• LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location.
• *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas.
• **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary.
• About LaunchDarkly:
• The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by:
• Improving the velocity and stability of software releases, without the fear of end customer outages
• Delivering targeted e

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