Full-Time Lead, Product Experimentation, Media Group

The Media Group at NBCU supports a powerhouse collection of consumer-first brands including Peacock, NBC, Bravo, NBC Sports, and NBCU International. With unequalled scale, our teams make the most of every opportunity to collaborate and learn from one another. We’re always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience. But most of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive.

As an individual contributor Lead for Statistical Inference & Research, you will serve as the principal architect and subject-matter expert for the experimentation platform’s statistical engine. You’ll design, implement, and optimize advanced statistical methodologies that underpin how we measure, learn, and innovate through experimentation.

Key Responsibilities

1. Statistical Engine Leadership: Design, maintain, and implement core inference capabilities (A/B, CUPED, sequential/adaptive methods, variance reduction, diagnostics) within our experimentation platform. Ensure all methodologies are robust, scalable, and production-ready.
2. Methodological Innovation & Signal Optimization: Conduct frequent statistical analysis on live and historical experiment data to optimize detection of real effects, reduce variance, and enhance signal purity. Research, prototype, and validate new statistical techniques, including handling zero-inflated data, covariate adjustment, multiple hypothesis correction, and causal inference. Lead the design and execution of simulations, backtests, and validation studies for inference engine upgrades.
3. Data Engineering Collaboration & Implementation: Build, optimize, and deploy statistical methodologies into production data pipelines and analytics workflows. Work directly with data engineering teams to define requirements, data models, and ensure successful scaling and integration of new methods.
4. Data Science Enablement: Mentor and guide analytics and data science teams on experimental design, statistical troubleshooting, and the use of advanced inference methods. Translate complex statistical innovations into clear technical documentation, best practices, and internal training resources. Advise on design and analysis of high-impact experiments across the company.
5. Technical Leadership & Roadmap: Identify platform opportunities and challenges; contribute to roadmap planning and technical strategy.

Required Skills & Experience

• 6+ years in experimentation science, applied statistics, data science, or data engineering, with significant experience in large-scale digital experimentation or analytics platforms.
• Deep expertise in statistical inference for experimentation (randomization, regression, variance reduction, sequential/adaptive methods, multiple hypothesis correction, causal inference, etc.).
• Hands-on experience implementing statistical models and methodologies in production data systems (SQL, Python, R, Spark, Databricks).
• Demonstrated ability to build and optimize data pipelines and workflows in partnership with data engineering.
• Proven skill in analyzing large and complex experimental datasets to inform and optimize inference methodologies.
• Excellent communication and documentation skills, with a track record of mentoring technical colleagues and cross-functional partners.
• Individual contributor technical leadership, ideally within experimentation, analytics, or data engineering teams.

Desired Characteristics

• Deep intellectual curiosity and drive to improve experimentation at scale.
• Technical rigor and a strong sense of ownership from research to production delivery.
• Collaborative, proactive, and skilled at working across engineering, data science, and analytics functions.
• Able to distill and communicate complex statistical concepts to technical audiences.
• Thrives in a high-velocity, innovative product organization.

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