Lead Data Analyst - Total Service (Operations)

Lead Data Analyst at Wise focuses on enabling data-driven decisions within Operations to scale servicing interventions and improve customer outcomes. You will own analytical capacity planning, data pipelines, and predictive modeling to support growth and operational excellence. Collaboration with workforce management, quality, training, and knowledge management is key to turning insights into real change. The role offers significant impact on how we resolve complex issues and optimize end-to-end processes. You will work in a mission-driven, data-enabled environment that values speed, reliability, and customer-centric metrics.

• Analytical capacity planning and forecasting to align with growth and demand
• Own data pipelines to ensure reliable, accurate data for high-stakes servicing interventions
• Develop predictive models and conduct cause-and-effect analysis to improve decisions
• Apply causal inference techniques (e.g., difference-in-differences, regression discontinuity, synthetic controls) for intervention evaluation
• Provide strategic insights into operational health, cost analysis, and key metrics including quality
• Monitor performance of strategic initiatives and identify optimization opportunities
• Lead KPI development and target-setting within reporting pipelines
• Collaborate with stakeholders to standardise forecasting, scheduling, and real-time operations

• Quantitative foundation in science or engineering
• Strong statistical mindset with ability to reason about distributions and significance
• 4+ years of analytics experience with strategic problem-solving
• Experience with operational analytics including capacity planning, forecasting, efficiency, quality, predictive analytics, and experimentation
• Proficient with complex data models in SQL (Snowflake) and analysis using Python or R
• Data visualization experience (Looker, PowerBI, Tableau) and ability to tell a story with data
• Bias to action and ability to drive initiatives
• Experience in operations domains and with WFM or quality teams is a plus
• Forecasting techniques such as ARIMA, Holt-Winters, and time series methods is a plus

• storytelling with data
• stakeholder collaboration
• proactive guidance on strategy
• SQL
• Python
• R