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Lead analytics for customer operations: build capacity planning and forecasting models, own data pipelines, develop predictive and causal inference analyses, track KPIs, standardise processes, and partner with operations, WFM, quality, and training to drive data-driven improvements.

Lead analysis of operational data to support decision-making. Build dashboards and reports, partner with operations stakeholders to identify process improvements, monitor KPIs, and inform strategic initiatives.

Lead procurement strategy for People & Workplace categories (recruitment, benefits, travel, facilities), manage a small procurement team, drive cost savings and supplier consolidation, implement sourcing and risk mitigation, improve processes and procurement technology, and partner with stakeholders to deliver commercial outcomes and compliance.

Lead development of a governance platform enabling Fraud, AML, KYC, Screening, and Compliance teams to build, monitor, and audit risk controls. Own data governance, control assurance, auditability, governance analytics, and regulatory readiness. Set KPIs, roadmap, and collaborate with Engineering, Data Science, Risk, and Audit to translate regulatory and technical requirements into scalable products.

Lead CRM analytics for Personal and Business segments: design measurement frameworks, run campaign and lifecycle analyses, apply A/B and incrementality testing, build segmentation models, maintain dashboards, ensure data quality, and partner with CRM, Product, and Data teams to optimise customer engagement and retention.

The Staff Data Analyst leads complex projects, develops scalable data solutions, and mentors other analysts while driving strategic initiatives at Wise.

Lead a team of backend and web engineers to evolve Wise's Account Details platform, build the receive-to-alias experience, shape the roadmap with Product, ensure high-quality distributed systems and web applications, mentor engineers, coordinate cross-team delivery, and participate in a 24/7 on-call rotation every ~6–10 weeks.

Lead product efforts to detect money laundering and related fincrime by building hyper-targeted, region-specific detection systems using machine learning and LLMs. Work with compliance, data scientists, engineers, designers and ops to define vision, roadmap, and measurable metrics (AML Recall and SAR Cost) while satisfying global regulatory requirements and improving automation and precision.

Build and maintain the Payin Platform that handles how money enters Wise. Design Payin Session and Payment abstractions, ensure reliability and scalability for high-volume transactions, collaborate across teams, write testable code, drive end-to-end ownership, and improve APIs and systems for excellent customer experience.

Lead analytics for Payment Operations risk: define KRI frameworks, set risk thresholds, build control assurance and reconciliation models, create reliable data pipelines and visualisations, and partner with risk and auditors to prevent financial loss and ensure compliance.