Top Data Analyst Jobs in London

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.

The Lead Data Analyst will analyze CRM data to improve marketing strategies, set KPIs, design testing methodologies, and maintain dashboards. This role involves collaboration with multiple teams to drive customer engagement and optimize marketing efforts.

The Lead Data Analyst will drive analytics efforts, enhance operations through insights, improve predictive models, and collaborate with teams to optimize performance and strategic initiatives.

The Senior Marketing Data Analyst will maintain the attribution model, ensure data accuracy, work with marketing and data teams, and provide insights 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.

The Lead Data Analyst will identify pricing and cost issues, conduct complex data analyses, improve pricing models, and monitor financial performance for Wise Platform.

Lead data strategy for the Credit Product team, manage data models, collaborate with stakeholders, and maintain high data quality in a fast-paced environment.

Lead the marketing data strategy, optimize acquisition spend, design data models, partner with teams for data-driven solutions, and maintain data quality.

Perform detailed analyses and statistical modelling of property and mortgage data, run portfolio valuations using the Hometrack AVM, build BI/visualisations, compile quantitative reports for clients, monitor model performance, answer analytical client queries, and support the analytics team.

The Marketing Data Analyst will analyze marketing data, optimize campaigns, support segmentation strategies, and build automated data pipelines while collaborating with various teams.

Measure and report member behaviour across digital pension platforms. Tag and validate data, analyse web analytics, create Power BI dashboards, support testing, monitor live performance, and collaborate with product, UX and data teams to inform personalisation and improvements.

Lead a commercial analytics team to deliver data-driven solutions that optimise revenue, margin, pricing and supply. Partner with trading, product, finance and engineering to build reports, visualisations (Looker), and data products, set quality standards, and guide strategic and tactical decision-making.

Transform procurement, cloud and infrastructure data into dashboards, forecasts and insights to support capacity planning, supplier management, cost optimisation and investment decisions. Build ETL pipelines, KPI frameworks and automated reporting, partnering with procurement, finance, engineering and operations and presenting findings to senior stakeholders.

As a Data Analyst, you will develop data solutions, conduct diagnostics and analysis for technical projects, and collaborate with clients to design effective outcomes.

Collect, clean, and transform large datasets; build and maintain data models and reports (using Snowflake and BI tools); perform statistical and machine-learning analyses; define KPIs; ensure data governance and accuracy; present insights to stakeholders; collaborate with data engineers and follow software development best practices.

Join the BDA team to support application development, analyze datasets for insights, and enhance analytical tools for stakeholder reporting.

Build and own data pipelines and metric definitions for finance reporting, map systems to the General Ledger, produce audit-ready data extracts, automate reporting integrations (Anaplan/Planful), and partner with Finance leadership to ensure consistent, accurate financial disclosures.

As a Data Analyst/Consultant, you'll undergo extensive training on data visualization and integration using Tableau and Alteryx, working with renowned clients to build your skills and confidence as a consultant.

The Data Analyst will ensure high-quality financial datasets by defining acceptance criteria, probing data quality, and collaborating with various teams. They will act as a subject-matter expert on data products and maintain a catalogue of datasets.

Hands-on data analyst role focused on operations analytics: build reporting baselines and dashboards, analyze workflows to find inefficiencies, use Python and SQL for deep-dive analysis, create proof-of-concept automations (APIs, LLMs), support QA/AML/fraud/customer support analyses, ensure data quality and metric consistency, and present insights to technical and non-technical stakeholders.

Perform data collection, analysis, and interpretation to identify trends. Build and maintain dashboards and reports, ensure data accuracy through quality checks, collaborate with teams to deliver actionable insights, and support development of analysis methodologies.

Support end-to-end processing of delegated bordereaux data (risk, premium, claims): validate, reconcile, monitor receipt, manage queries with third parties, contribute to MI/reporting, and drive process standardisation and continuous improvement to reduce manual work.

Produce ecommerce insights across the customer journey using SQL and Python. Build cohort, LTV, segmentation, funnel and A/B test analyses. Create Looker dashboards, partner with product/commercial/data engineering, surface data quality gaps, and translate findings into actionable recommendations for stakeholders.

Generate ecommerce insights across the customer journey through cohort analysis, segmentation, LTV modelling, funnel and A/B test analysis. Track core ecommerce metrics, evaluate feature and pricing performance, build Looker dashboards, and collaborate with product, commercial and data engineering teams to translate analytical findings into actionable recommendations for stakeholders.

Analyze product and user behaviour across multiple data sources to identify trends, diagnose issues, and recommend improvements. Build dashboards and visualisations, track KPIs, support A/B testing and experimentation, and collaborate with product, engineering and analytics teams to improve digital healthcare journeys while maintaining data quality and governance.