Now, we're on the lookout for a Data Science Manager to lead the team powering our internal experimentation platform - a critical pillar of how we test, learn, and improve the travel experience for millions!About the roleHybridThis is a high-impact leadership role focused on enabling smarter, faster decisions across Skyscanner. You'll lead the team behind WISE - our in-house experimentation platform - developing the tools, frameworks and statistical features that help teams across the business explore new ideas with confidence.You'll work at the intersection of data science, engineering, and product, guiding both technical delivery and team growth. The scope extends beyond experimentation too - into areas like anomaly detection, forecasting, and bot detection - helping improve performance, reliability and decision quality at scale.What you'll be doingLeading and growing a team of data scientists focused on experimentation enablement, internal analytics tooling, and measurementDeveloping and maintaining WISE, Skyscanner's experimentation library - ensuring statistical rigour, scalability, and usability across teamsCollaborating with product managers and engineers to define features, deliver PoCs, and bring statistical tooling into productionDesigning advanced statistical features such as Bayesian methods, sequential testing and causal inference to support evolving experimentation needsPromoting experimentation best practices across the business - shaping how Skyscanner tests and learnsSupporting internal measurement initiatives like anomaly detection, forecasting and LTV modelling - from ideation through to deploymentFostering a team culture grounded in learning, curiosity, and high standards in both statistical thinking and software developmentRepresenting the team in cross-functional forums, advocating for experimentation and internal tooling as key strategic enablersAbout youExperienced leader: You've led high-performing data science teams, ideally in experimentation, statistical infrastructure or internal analytics platformsStatistically strong: You have deep knowledge of experimental design, Bayesian statistics and causal inference - and know how to apply them at scaleTechnically sharp: Proficient in Python and SQL, with hands-on experience in statistical programming. Familiarity with Airflow, Spark and cloud platforms (GCP/AWS) is a plusPlatform-aware: You're comfortable working with engineers to bridge the gap between prototypes and production-grade toolingMeasurement minded: You're fluent in the concepts that sit around experimentation - from anomaly detection to forecasting - and how they shape business performanceStrategic stakeholder manager: You influence product direction, shape priorities, and communicate complex ideas clearly to varied audiencesSupportive mentor: You're passionate about coaching others, creating a team environment that values autonomy, psychological safety and growthBalance focused: You're skilled at delivering near-term impact while investing in long-term platform quality, experimentation confidence and team healthEnd-to-end thinker: You've worked across the full data science lifecycle - from exploration and measurement to production and iteration * Sustainability and accessibility focused: You think in systems and solutions, always aiming for simplicity, inclusivity and long- term value.#LI-FM1
