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External opportunity

Lead Data Analyst, Customer Support

London, United Kingdom Full-time

£75,000–115,000 per year

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Posted 4 Nov 2026 · Engineering

Job description

Job Description We are looking for a Lead Data Analyst who is passionate about our mission of Money Without Borders. You will partner with our Customer Support organisation to help drive data-driven decisions that improve customer outcomes while managing cost to serve and team capacity. Customer Support is the largest customer-facing area in Servicing. It is where cost to serve, AI and automation, and the alignment between Operations and Product come together. You will measure whether changes to channels, self-serve flows and AI agents are working for customers, and you will be a trusted analytical voice for CS Operations, CS Product and WFM. As a Lead Data Analyst, you will own key parts of the customer support metric tree, measure the impact of automation and AI, and run experiments and causal analyses that show what really changed. You will also help make sure the team's metrics are defined once, owned clearly and trusted by everyone who uses them. This is a great opportunity for an analyst who has a keen understanding of customer problems, strong product thinking and is passionate about creating convincing analyses. You will also be part of the Servicing Analytics community of 86 analysts and a wider community of 150+ analysts at Wise, where you can collaborate on cross-team projects, share knowledge and help improve how analytics works across the company.  This is an IC3 role. For more information on our Analytics Career Map and levelling structure, click here. WHAT YOU'LL BE DOING Collaborate with senior stakeholders across Customer Support and effectively communicate your insights into real change for our customers. Join us in working towards our mission. Own key areas of the CS metric tree, for example contact rate, first response, resolution, CSAT, repeat contact and cost per contact, and make sure they roll up cleanly into Servicing's Cost and Convenience toplines. Support target-setting and tracking with Ops and Product leaders, so the team can see whether targets are being hit, not just set them. Measure AI agent, self-serve and deflection impact. Estimate addressable volume, actual deflection and cost saved, and the effect on CSAT, repeat contact and quality. Monitor automation quality. Support calibration and drift monitoring on quality scoring so automated decisions stay trustworthy. Support capacity planning and forecasting with WFM, including demand forecasts, staffing models, SLA and wait-time trade-offs, and regional and outsourcing mix. Make trade-offs explicit. Show the impact on customer outcomes, operational cost and team capacity in every channel and staffing recommendation. Build and maintain high-quality data models and pipelines in SQL and dbt, and review analytical work from colleagues to keep the bar high. Qualifications You have experience with SQL and building data pipelines (dbt experience is preferable). You are confident working with complex data models and are able to independently design and implement new models. You have strong quantitative skills. Ideally a background in statistics, mathematics, physics, engineering, analytics, computing, or any other scientific areas. You have strong communication skills and an ability to translate business insights into persuasive analytical narratives that are simple to understand and that drives customer impact. You have an ability to structure business problems with minimal supervision and prioritise problems collaboratively with stakeholders. You take ownership of your own impact on our customers. Be proactive. You go beyond just the analysis and get things done. You have experience with data visualisation tools (Looker, PowerBI, Tableau etc.) and demonstrate confident storytelling ability with data. 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. Python Additional Information 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. 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. 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.
Pay, skills & work eligibility

Compensation

£75,000–115,000 per year

Pay basis not specified

Stated in original posting data. No currency conversion or estimated salary.

View compensation wording
Original posting compensation: min 75000; max 115000; currency GBP; period YEARLY.

Location, eligibility & working hours

Listed work location
London, United Kingdom
Visa sponsorship
Not stated clearly
Relocation support
Not stated clearly
Working hours / time zone
Not stated clearly

Remote does not automatically mean work from any country. A location match does not confirm work authorization, sponsorship or relocation eligibility.

Requirements at a glance

PythonSQLPower BI · requirementTableau · requirementCustomer supportCommunication

Named skills identified in the listing. A mention is not always a requirement; read the full description and employer conditions.

Location & work arrangement

Listed work locations

  • Worship Square, 65 Clifton Street, London, EC2A 4JE, United Kingdom

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