Senior Director of Analytics - Operations in London

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. We believe teams are strongest when they are diverse, equitable and inclusive.

We're looking for a Senior Analytics Director to accelerate Operations Analytics from a primarily reactive partner to a strategic, outcome‐driving function. You'll shape the "big rock" agenda for our Operations and Mitigations squads, represent analytics at the Product Engineering leadership table, and scale a high‐performing team through a period of significant growth. This is a hands‐on role where you'll manage three teams: Customer Support Analytics, KYC Analytics, and Onboarding Analytics. We're looking for a leader who balances people, product, systems, and operations thinking—and who can turn data into direction months ahead of the curve.

What You'll Do

• Drive strategic analytics by shifting the function from reactive reporting to proactive, strategic insight and decision support.
• Own the analytics narrative and actions in Monthly and Quarterly Business Reviews; ensure we drive sharp, measurable outcomes.
• Build a culture of deeper analytical dives, clear problem‐framing, and robust experimentation.
• Represent analytics on the Product Engineering leadership team; partner with engineering leaders on system design, data as a product, instrumentation to make analytics a first‐class citizen.
• Help architect a more scalable, defect‐free onboarding experience; guide automation at scale, A/B testing strategy, and Pareto‐driven cost and quality improvements.
• Work with Ops leaders on upstream resolution for contacts and complaints, and on the right mix of regional vs. global processes.
• Define and measure granular SLAs that reflect customer impact.
• Strengthen end‐to‐end forecasting, capacity, and productivity modeling.
• Improve vendor performance management and accountability.
• Identify and prioritise automation opportunities tied to clear business value.
• Help hire and onboard 20+ new team members as we migrate BI and expand Analytics; maintaining consistently high hiring bar.
• Put in place scalable performance, coaching, and prioritisation practices for a larger, multi‐team analytics organisation.
• Coach leads through growth challenges, role changes, and, when needed, performance management with clarity and care.
• Establish consistent stewardship of our data assets and analytics platforms.
• Be a trusted deputy for the Head of Servicing Analytics; ensure the org runs smoothly in their absence and as scope grows to 80+ across Analytics (excluding DS and Analytics Engineering).

What Success Looks Like In The First Year

• A clear, prioritised "big rocks" roadmap with measurable wins across SLAs, forecasting accuracy, vendor performance, automation throughput, and onboarding scalability.
• Sharper MBR/QBR decision‐making and outcomes driven by analytics.
• A resilient org design with a strong leadership bench, 20+ high‐quality hires onboarded, and consistent performance practices.
• Analytics embedded in system design; reliable, well‐governed data assets; a proactive insights program that shapes 6+ month direction.

Why join?

A culture of supportive attainment: high performance paired with genuine care for the people who make it happen. Freedom to shape strategy, organisation, and systems—while holding a high bar for data products, analytics quality, and business impact.

Qualifications

• Ideally you will have experience working in a high‐growth technology organisation.
• Proven experience managing leaders in analytics or adjacent data functions.
• A track record of setting organisational direction and delivering outcomes on 6+ month horizons.
• Exceptional communication and stakeholder influence across Operations, Product, and Engineering.
• Demonstrated ability to move a function from reactive to proactive insights and decision support.
• Ownership of analytics data infrastructure and strong familiarity with data‐as‐a‐product principles; comfortable in system design conversations with engineering.
• Strength in balancing multi‐objective operational trade‐offs (e.g., SLAs, cost, productivity, quality).

Nice to Have

• Experience partnering with or leading ML‐adjacent teams.
• Experience building 0→1 teams across multiple geographies.