Data Scientist 6 - Experimentation Platform

XP Strategy & Influence: Help set the strategy for the Experimentation Platform, including UI design, and user flows. Define how data scientists contribute metrics, reports, and templates to the platform so they have high leverage when setting standards for experiments in their own space. Trust & Methodology: Verify that XP allocates, logs, and processes data using valid, trustworthy causal inference methods, and demonstrate that trustworthiness to partner teams - turning verification into automated, recurring, monitored practice rather than one-off checks. Bridge the gap between data science requirements and platform engineering implementation, representing the DS organization's needs directly to engineering leadership. Lead the consolidation of fragmented, bespoke experimentation systems into a coherent, maintainable platform by building the tools and processes that make best practice the path of least resistance. Mentor and raise the bar for other team members working on or with the platform, and represent XP's point of view in company-wide discussions on experimentation methodology. Advanced degree (PhD or Masters) in Computer Science, Statistics, Economics, Applied Mathematics, or a related quantitative field. 8+ years of experience with statistics / causal inference in an experimentation context, including designing experiments at scale and diagnosing them when they break. Demonstrated track record of setting standards or building tools that were adopted across multiple teams or an entire organization - not just applying judgment project by project. Deep, practical knowledge of experimentation pitfalls and how to guard against them at a program level: sample ratio mismatches, winner's curse and regression to the mean, false discovery rate across a portfolio of tests, peeking, covariate adjustment, and allocation-vs-analysis-unit mismatches. Experience translating ambiguous data science pain points into a sequenced product roadmap, including judgment on what a platform should build in, expose as a self-serve primitive, or explicitly not support. 5+ years experience with data science languages, ideally including Python and SQL; comfort partnering closely with engineers on API/schema/system design. Excellent cross-functional communication skills, with a demonstrated ability to influence skeptical stakeholders - both highly technical (data scientists, engineers) and non-technical business partners to adopt new methods or standards. Curiosity to learn new statistics, methods, and optimization techniques, and the judgment to know when established methods are the better choice.