Top Data Analyst Jobs in London

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.

Support end-to-end data lifecycle for compliance by turning business problems into validated data assets: gather requirements, create data dictionaries and mappings, map processes, write and optimize SQL, perform EDA, run UAT tests, build and maintain BI visualizations (Tableau/Mode/PowerBI), and monitor dashboard performance.

Partner with engineering and product leaders to define, measure, and improve platform reliability. Connect system signals (incidents, performance, failure modes) to customer and business impact, build metrics, dashboards, and frameworks, and influence investments to improve platform stability and outcomes.

Maintain and enhance marketing attribution models and data pipelines (dbt), ensure data integrity, build dashboards for stakeholders, run in-depth analyses, and translate results into strategic recommendations to improve marketing effectiveness.

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

Lead growth & adoption analytics by building and maintaining agent-ready curated datasets, partnering with engineers and product teams, reviewing merge requests, defining pipelines and metrics, performing advanced SQL analyses on petabyte-scale data, and communicating actionable insights to stakeholders.

Support investment teams by acquiring, cleaning, and analyzing multi-source data to test investment theses, identify inflection points, and present research. Learn fundamental investor approaches, build decision-support tools, and communicate findings clearly to Sector Data Analysts and investment teams.

Lead pricing analytics for Wise Platform: define and investigate pricing and cost problems, analyze product economics and P&L, improve data quality and allocation methodologies, influence pricing model enhancements, and surface actionable insights for profitability and growth.

The Payments Data Analyst will manage the payments data lifecycle, delivering insights to enhance performance, support commercial decisions, and facilitate partnerships across teams while ensuring data quality and accessibility through analytics tools.

Lead analytics for FinCrime operations: own forecasting and capacity planning, maintain data pipelines, build predictive and causal models, assess operational health and costs, implement KPI frameworks, track initiative performance, and standardise processes across forecasting, scheduling, and real-time operations.

You'll partner with senior leaders to define and improve reliability metrics, influencing decisions based on data insights and system performance.

Drive analytics for Payment Operations to improve payment quality and efficiency. Build attribution models for quality lapses, incorporate AI into review processes, expose and visualise payment data, create reports and pipelines, track KPIs, and collaborate with senior stakeholders to turn insights into operational 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 end-to-end delivery of compliance data products: translate business needs into specs, map sources, define KPIs, design transformations with data engineers, run UAT, and build insightful dashboards to drive stakeholder decisions.

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.

Lead the measurement and insight function for a flagship loyalty programme: set metric definitions, design incrementality and control-group testing, own analytics roadmap and standards, translate findings to stakeholders, own predictive models and forecasting, and assure analytical quality across multi-party delivery to demonstrate commercial value.

Partner with Product, Design, Engineering, and Analytics Engineering to analyze customer behaviour and product performance using funnel, cohort, and segmentation analyses; define and monitor KPIs; design and analyze A/B tests; build dashboards and reports; surface trends and recommendations; and apply AI/ML (including LLM-assisted) techniques to speed insight generation and measurement.

Lead a hands-on analytics role to design and build a scalable cost-to-serve model, integrate and transform multi-source data, ensure data quality, run scenario and statistical models, and translate outputs into actionable operational excellence insights for stakeholders.

Analyze campaign and business performance data, develop KPIs and measurement frameworks, produce regular and ad-hoc reports, translate complex datasets into actionable insights, and collaborate with cross-functional teams to improve campaign performance and reporting methodologies.

Work directly with customers to onboard datasets, design synthetic population queries, diagnose and improve data pipelines, validate synthetic methodologies, lead technical engagements, train and document for adoption, and feed customer insights into product priorities.

Design, build, and maintain reporting and visualization solutions. Analyze stakeholder requirements, develop data models and ETL pipelines, deploy BI reports, document requirements, support data warehousing architecture, and train business users to drive data-driven decisions.

Design, build, and maintain scalable backend services, data pipelines, and integrations to support accounting, reconciliation, and financial reporting. Partner with Finance and Accounting to translate regulatory and audit requirements into reliable, auditable systems, mentor junior engineers, and improve data accuracy, pipeline reliability, and system performance in a compliance-critical environment.

Design, build, and maintain BI reporting and visualizations; perform data modelling and ETL; collaborate with commercial stakeholders to surface insights; support data warehouse architecture and governance; train users and document BI solutions.

Perform ad-hoc analyses, identify trends and anomalies, and present insights. Build and maintain Looker dashboards and automated reports, write optimized SQL, collaborate on data modelling/dbt, ensure data quality, and partner with stakeholders to drive data-informed decisions that improve patient outcomes.

Generate insights to inform company and customer decisions by curating datasets, surfacing metrics, performing statistical modelling, and deep-dive analysis. Analyze growth drivers, customer segments and cohorts, and link acquisition/activity to marketing and product initiatives to measure realised financial returns. Communicate findings through data visualisation and stakeholder management.