Lead Data Analyst - Total Service (Operations)

We’re looking for a Lead Data Analyst who is passionate about our mission of Money Without Borders to partner with our operational teams to help drive data-driven decisions that would support our fast-growing product through scaling and optimising the team.

As a Lead Data Analyst, you’ll drive analytics within a dedicated customer operations model where we improve how we resolve complex and time‑sensitive customer issues—speed, reliability, quality, and end‑to‑end outcomes—and scale what works across our wider Operations teams

Most importantly, you’ll collaborate closely with your operational leads, as well as workforce management, quality, training, and knowledge management, to bring your insights into real change for our customers and help drive our mission!

Analytical Capacity Planning and Forecasting. Focus on building and refining analytical models for strategic capacity planning. Take ownership of forecasting efforts to align with business growth and operational demands.

Data Pipeline Ownership. Take ownership of data pipelines to maintain and improve data flow, ensuring reliability and accuracy of data that drives high-stakes servicing interventions at scale.

Predictive Modeling and Cause and Effect Analysis. Develop and implement robust models to predict outcomes and perform cause and effect analysis to identify key drivers, optimise processes, and enhance decision-making and strategic planning.

Causal Inference and Quasi-Experimental Analysis. Develop robust approaches to cause-and-effect analysis in an environment where A/B testing is potentially feasible - applying techniques such as difference-in-differences, regression discontinuity, or synthetic controls to evaluate the true impact of servicing interventions and confidently attribute outcomes without waiting for ideal conditions.

Strategic Support and Analysis. Provide critical insights to assess the operational health of the Total Services function, conduct in-depth cost analysis, and offer detailed analysis of operational metrics (including quality) to understand impacts on customer experiences.