Top Data Analyst Jobs in London

Analyze paid social audience and platform performance data, design experiments, optimize budgets, and identify measurement improvements. Own dbt data pipelines, monitor data quality, and maintain BI dashboards in Looker or Lightdash. Develop analytical frameworks, investigate anomalies, and communicate insights, risks, and trade-offs to Paid Social and cross-functional teams. Apply attribution, unit economics, incrementality, and marketing measurement expertise across platforms including Meta, TikTok, Reddit, and Snapchat.

Own and measure Cloud Platform metrics end-to-end, define targets and coverage, build dashboards and frameworks, enable data-informed decisions, and influence engineering leadership to improve reliability, cost, and productivity.

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.

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

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.

Own end-to-end analytical projects, including scoping business problems, KPI monitoring, dashboard and notebook development, root-cause analysis, and insight delivery. Build production-quality SQL and Python, maintain Looker dashboards and Hex notebooks, investigate data discrepancies, communicate recommendations, and collaborate with Analytics Engineers on new data sources. Use AI tools responsibly to accelerate analysis while ensuring accuracy, quality, and repeatability.

Own B2C marketing KPIs, reporting, acquisition funnel analysis, attribution, measurement studies, tracking, and self-serve data products. Use SQL and Python to generate actionable growth insights, improve marketing measurement, activate customer data, and develop AI-powered analytics solutions. Partner cross-functionally with Marketing, Product, and Data teams while ensuring tracking accuracy and regulatory compliance.

Lead the creation of Market Data Operations, manage Bloomberg and LSEG entitlements, maintain security master and identifier mappings, track enterprise data usage and costs, support exchange declarations/audits, resolve data quality issues, automate workflows, and provide stakeholder support for portfolio managers, traders, researchers and data teams.

Analyze large and unstructured datasets using SQL and visualization tools such as Tableau or Looker. Support finance and business decision-making through rigorous analysis, data testing, mapping, and migration activities. Communicate insights clearly, collaborate with stakeholders, maintain data privacy and security standards, and contribute to system testing and team projects with guidance.

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.

Analyzes gym trading performance, membership acquisition and retention, location performance, product performance, and member behavior. Builds dashboards and reports, answers ad hoc commercial questions, scopes analysis, and presents actionable insights to technical and non-technical stakeholders. The role supports strategic growth, investment, customer experience, and operational decision-making across the business.

Partner with Product, Design, Engineering and Analytics Engineering to analyze customer behaviour, define KPIs, run funnel/cohort analyses, design and evaluate A/B tests, build dashboards, and surface actionable product insights to drive activation, engagement and retention.

Supports the Client Experience, Data & Insights team by analyzing marketing, client, CRM, and digital data. Develops dashboards, reports, customer insights, and marketing analytics to improve client experience and commercial outcomes. Collaborates across global teams while building skills in data visualization, SQL, analytics tools, data governance, and AI-enabled reporting.

As a Senior Data Analyst, you will gather and document business requirements, manage stakeholders, analyze complex datasets, and create data models and dashboards.

As Lead Data Analyst, you will monitor and ensure the accuracy of forecasting models, diagnose forecasting errors, and communicate findings to stakeholders for operational improvement.

Partner with Product and Engineering to define metrics, run root-cause analyses and experiments, build tracking, reporting, and automated alerts, model data in dbt/BigQuery, scale AI-assisted analytics for self-serve, and communicate insights to drive product and business 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 last-mile geospatial analytics to optimise routing, network planning, forecasting and capacity. Build statistical and ML models, create Looker dashboards, track performance, and integrate analytics into operations. Partner with leadership and international partners, mentor colleagues, and drive data-driven strategies that reduce cost and carbon emissions.

Lead Data Analyst responsible for advanced analytics, quantitative analysis, experimentation, and commercial modeling. Partner with Data Engineering to implement scalable pipelines, drive insights into decision-making, and embed customer research into operations. Mentor analysts, build data literacy, and influence cross-functional strategic and tactical decisions.

Join the Integration team to collect, validate, map and load high-volume financial data from clients into SteelEye's analytics platform. Engage stakeholders, resolve data queries, refine operational processes, and perform industry research to meet data quality metrics.

Deliver actionable, data-driven insights and self-serve reports across brands. Build and optimise data sources, monitor experiments, create KPIs, automate processes, and work with data engineers to productionise outputs while communicating findings to stakeholders.