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.

Director of Analytics - Customer Support

Job Description