Senior Statistician

Overview

In this role you will advance statistical accuracy across Optimizely’s experimentation platform, collaborate with product and engineering teams to develop new statistics and ML features, and educate stakeholders through webinars and papers. You’ll partner with academia to explore trends and drive innovations in measurement and inference. You will also engage customers to explain methodologies and help design statistically valid experiments. This position blends hands-on analytics, thought leadership, and cross-functional influence to shape cutting-edge marketing technology.

Responsibilities

• Collaborate with product managers and engineers to design and implement statistical and ML features across the product suite
• Test and validate new statistical methods and integrate them into the platform
• Analyze product data to optimize features and provide actionable improvements
• Leverage AI agents to deploy new statistical capabilities
• Partner with academia and industry researchers to explore advanced methods
• Identify trends in experimentation and statistics to enhance offerings
• Propose and prototype techniques to solve customer problems
• Develop and enforce statistical standards and best practices
• Monitor algorithms for accuracy, reliability, and scalability
• Provide guidance on statistical compliance to safeguard results
• Create educational content (webinars, blogs, white papers) and present at conferences
• Explain statistical concepts to technical and non-technical audiences
• Represent Optimizely at events showcasing expertise
• Conduct customer calls to explain how accuracy is maintained and address inquiries
• Assist customers in designing statistically valid experiments
• Collaborate with sales, customer success, and onboarding to offer statistical expertise
• Foster a data-driven decision-making culture

Key requirements

• 3+ years of experience in experimentation, data science, or analytics
• Strong understanding of experimentation, RCTs, and inference, including multiple hypothesis and sequential testing
• Experience with classical, Bayesian, causal inference, or reinforcement learning methods
• Hands-on experience with Python and SQL; knowledge of R is helpful
• Experience applying statistical research or designing commercial statistical features
• Experience with AI applications

• Communicating effectively
• Interacting with people at different levels
• Cross-functional collaboration
• Classical and Bayesian statistical inference
• Causal inference and experimental design
• Reinforcement learning (multi-armed bandit)

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