Director of Analytics - Customer Support

Customer Support is the largest customer-facing area in Servicing. It is also where cost to serve, AI and automation, and the alignment between Operations and Product meet. We're looking for a Head of Customer Service Analytics who is passionate about our mission of Money Without Borders. You will lead all analytics for Wise's customer support operation: CS Ops, CS Product, and WFM and capacity planning. You'll be accountable for the CS metric tree and for measuring the impact of automation and AI. You'll also build a team that improves CS cost and customer outcomes together, rather than trading one off against the other. Analytics at Wise is a core leadership engine, not a service desk. You'll be a strategic peer to CS Operations and CS Product leadership. You'll co-author OKRs, broker trade-offs between Ops and Product, and be the analytical voice in the room.

You'll lead a team of around 9 analysts and WFM specialists across London, Tallinn and Budapest, and build its first layer of analytics leads (AL2). You'll sit within the Ops & Mitigation analytics leadership group, as part of the 86-strong Servicing Analytics community and a wider community of 150+ analysts at Wise. This is an AL3 role. For more information on our Analytics Career Map and levelling structure, click here. WHAT YOU’LL BE DOING

• Own the CS metric tree: contact rate → channel → first response → resolution → CSAT / repeat contact → cost per contact. It should roll up cleanly into Servicing's Cost and Convenience toplines.
• Make sure every CS metric has one definition and one owner in the metric store, and retire conflicting legacy dashboards.
• Set and govern CS targets with Ops and Product leadership, so we can show whether targets are being hit, not just set them.
• Own impact measurement for AI agents, self-serve and contact deflection: addressable volume, actual deflection, cost saved, and the effect on CSAT, repeat contact and quality.
• Run the experimentation and causal-inference approach for CS. Use A/B tests for customer-facing changes. Use diff-in-diff, RDD or synthetic control for ops rollouts.
• Keep automation quality trustworthy through calibration and drift monitoring on quality scoring.
• Own CS capacity planning and forecasting with WFM: demand forecasts, staffing models, SLA and wait-time trade-offs, and regional and outsourcing mix.
• Hold the three-way trade-off of customer outcomes, operational cost and team capacity, and make it explicit in every channel and staffing decision.
• Lead, coach and grow the team, and build its first AL2 layer. Set the bar for analytical quality and stakeholder impact.
• Own the CS analytics headcount plan and hiring. Sit on Servicing Analytics leadership and hiring panels.
• Shift analyst time from recurring reporting towards decision-driving work, by moving reporting into the metric store and self-serve.