Top Data & Analytics Jobs in London

Analyze customer, product, and market data to identify friction and new sending opportunities. Partner with Product Managers and Engineers to size opportunities, prioritize features, define success metrics, design experiments, and evaluate product changes. Translate complex analysis into clear recommendations that guide product strategy and decisions. The role also contributes to launching new products, improving instrumentation, and building reliable data transformations and pipelines.

Lead analytics for security, risk, and compliance controls. Build and optimize Python, SQL, dbt, Airflow, and REST API data pipelines; develop continuous control monitoring metrics, dashboards, and efficiency frameworks; investigate data quality and SLA issues; partner with security, compliance, product, engineering, and risk teams; and manage one or two analysts.

Design and build low-latency, real-time liquidity observability systems and streaming data pipelines for global financial operations. Architect Kafka and Flink pipelines, develop real-time aggregation and event-driven architectures, model streaming and analytical data, and ensure reliability through idempotency, exactly-once processing, failure recovery, and schema evolution. Collaborate with product, data science, quantitative analysis, and treasury teams to support liquidity positioning, forecasting, and operational visibility.

Lead data analytics for Treasury Operations by analyzing performance, automating processes, building dbt data models, and maintaining Lightdash dashboards. The role supports corporate treasury and banking-partner decisions, translates business needs into analytical solutions, collaborates across finance and engineering, and mentors analysts while ensuring accurate, reproducible work.

Lead data architecture and engineering for Wise’s marketing platform. Build scalable streaming and batch pipelines, productionize customer data workflows using Airflow and dbt, improve reliability and data quality, and bring MarTech integrations in-house. Partner with engineering, analytics, product, and marketing teams to scope ambiguous problems and deliver robust solutions. Mentor software engineers on data engineering best practices, architecture, and implementation.

Leads analytics for Wise’s Business Account Squad, managing a team of 5+ analysts embedded in product teams. Partners with Product, Engineering, and Design to identify opportunities, define KPIs, evaluate product impact, and guide roadmap decisions. Owns the analytics data strategy, develops scalable data tools, communicates progress, and drives action. Responsibilities also include coaching, performance management, hiring, capacity planning, and stakeholder management.

Lead data analysis for Wise Business Operations, deriving insights that shape strategy and product decisions. Define KPIs, build dashboards and automated data pipelines, identify high-impact opportunities, and lead cross-team analysis of servicing friction and customer retention. The role requires strong stakeholder influence, clear communication, independent ownership, and the ability to turn complex data into actionable recommendations.

Own marketing analytics reporting and infrastructure that explain growth drivers and identify high-value opportunities. Develop automated insights, Marketing Financials tooling, Lightdash reports, Streamlit applications, semantic layers, impact calculations, and AI-enabled workflows. Partner with marketing, analytics, product, and regional teams to convert insights into execution, while improving prioritization, collaboration, data quality, and analytics team processes.

Lead the Pricing Analytics team, manage and improve Wise’s pricing model, and guide strategic pricing decisions. Oversee analysts working on datasets, metrics, statistical modeling, and analysis. Partner with Finance, Product, commercial, and cost owners to analyze profitability, allocate costs, improve data quality, and translate business needs into actionable insights. Build scalable data models and pipelines while influencing company and product priorities.

Lead Wise’s Enterprise Risk Analytics strategy, roadmap, and team. Build standardized risk metrics, governance, reporting, data pipelines, monitoring, and audit-ready measurement frameworks. Partner with Data and Engineering to establish reliable models and lineage, quantify risk and business trade-offs, and drive insight-to-action decisions across financial, financial crime, operations, resilience, and regulatory stakeholders. The role also requires strong first- and second-line governance leadership in a regulated fintech environment.