Director of Analytics – Customer Support

Overview

In this role you lead Wise’s customer service analytics, shaping how CS Ops, CS Product, and WFM drive outcomes. You own the CS metric framework, measure automation impact, and steer data-driven decisions that balance customer outcomes with cost. You’ll build and grow a high-performing analytics team across multiple hubs and partner with leadership to set strategy and OKRs. This is a mission-critical function that treats analytics as a strategic engine rather than a back-office service. You help Wise scale analytics to support customers globally.

Responsibilities

• Own and standardize the CS metric tree (e.g., contact rate, first response, resolution, CSAT, cost per contact) and ensure clear ownership across the metric store.
• Govern CS targets with Ops and Product leadership and track performance against them.
• Measure impact of AI agents, self-serve and contact deflection on CS metrics and customer outcomes.
• Lead experimentation and causal inference approaches (A/B tests, diff-in-diff, RDD, synthetic control) for CS initiatives and ops rollouts.
• Ensure automation quality with calibration and drift monitoring on quality scoring.
• Oversee CS capacity planning and forecasting with WFM (demand, staffing, SLA, wait times, outsourcing mix).
• Navigate trade-offs between customer outcomes, operating costs, and team capacity in all channel decisions.
• Lead, coach, and grow the analytics team, establishing the first AL2 layer and setting high analytical standards.
• Own headcount planning and participate in Servicing Analytics leadership and hiring panels.
• Shift focus from recurring reporting to decision-driving work by consolidating reports into the metric store and enabling self-serve.

Key requirements

• Significant experience leading analytics teams, with a track record of building and developing high-performing teams.
• Strong strategic and product thinking with the ability to structure ambiguous problems and influence senior stakeholders.
• Strong quantitative background (statistics, mathematics, engineering, or related field) with hands-on SQL experience (dbt preferred) and complex data models.
• Experience with experimentation and causal inference and defining metrics/KPIs frameworks.
• Excellent communication and influencing skills, with ability to tell persuasive data-driven stories to executives.
• Experience with data visualization tools (Looker, Tableau, Power BI) and data storytelling.
• Proactive, ownership mindset and willingness to drive impact beyond analysis.

• strong communication
• stakeholder influence
• proactive ownership
• SQL
• dbt
• data modeling

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