The posting
Company Description
Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
More about our mission and what we offer.
Job Description
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.
Qualifications
- Significant experience leading analytics teams, ideally including leading other analytics leads or managers. You have a track record of building and developing high-performing teams.
- Strong strategic and product thinking. You can structure ambiguous business problems with minimal supervision, prioritise with senior stakeholders, and shape direction instead of just answering questions.
- Strong quantitative background (statistics, mathematics, physics, engineering, computing or a related field). You have hands-on experience with SQL, ideally dbt, and complex data models. You can review and challenge the technical work of your team.
- Experience with experimentation and causal inference, and with defining metrics and KPI frameworks.
- Excellent communication and influencing skills. You can build persuasive narratives from data for senior and executive audiences and drive real change.
- Experience with data visualisation tools (Looker, Tableau, Power BI, etc.) and strong data storytelling.
- You are proactive, take ownership of your impact on customers, and go beyond the analysis to get things done.
NICE TO HAVE BUT NOT ESSENTIAL
- Experience in customer support, customer experience or operations analytics (contact demand, WFM, QA, CSAT, cost-to-serve).
- Experience applying AI or LLMs to support or analytics workflows.
- Fintech or payments experience.
Additional Information
For everyone, everywhere. We are people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We are proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences.
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
