Senior Data Science Manager (Experimentation)

Role overview The Senior Data Science Manager (Experimentation) is a senior technical and organizational leader responsible for the health, velocity, quality, and governance of experimentation practice across a global product organization. Operating within a Product Data Science function that supports large-scale travel and experiences marketplaces, the role owns the end-to-end experimentation operating system and raises the bar for how teams design, run, and interpret tests.

Responsibilities - Own the experimentation operating system, including governance, standards, lifecycle, and quality controls across all tests. - Define and enforce standards for experiment design, metric selection, statistical validity, and metadata completeness. - Drive balanced experimentation coverage across product surfaces and improve velocity by eliminating systemic failure modes. - Establish a single source of truth for experimentation health so leadership can see what is being tested, where, and with what outcomes. - Partner with Product, Engineering, Data Engineering, and Product Data Science leadership to align priorities and resolve system-level issues. - Scale frameworks, documentation, and tooling that make correct experimentation the default across product teams.

Requirements - Extensive experience in data science, experimentation, product analytics, or a related quantitative discipline in a product-led organization. - Strong proficiency in SQL and Python with deep understanding of A/B testing, causal inference, and applied experimentation frameworks. - Demonstrated systems thinking across governance, tooling, processes, and organizational behavior. - Strong product acumen and the ability to influence prioritization and roadmap decisions through experimentation insight. - Proven success influencing senior stakeholders across Product, Engineering, and Data without direct authority. - Experience scaling experimentation velocity, quality, and adoption through structural interventions.

Nice to have - Experience improving experimentation operating models at scale rather than only running individual experiments. - Background in high-scale marketplaces, e-commerce, or travel platforms. - Hands-on familiarity with SaaS experimentation tools such as Statsig, Eppo, or GrowthBook. - A reputation for improving how organizations make decisions, not just the quality of individual analyses.

Benefits and work setup - Remote-friendly working model with flexible scheduling and a focus on work-life balance. - Competitive compensation including base salary and annual bonus. - Health benefits, an employee assistance program, and a generous referral scheme. - Annual lifestyle benefit, donation matching, and tuition assistance for qualifying programs. - Travel-related perks and discounts for employees.