Top Data Analyst Jobs in London

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 analytics for FinCrime operations by building capacity-planning forecasts, owning reliable data pipelines, developing predictive and causal models, analyzing costs and operational health, tracking strategic initiatives, and establishing KPI frameworks. The role partners with workforce management, quality, training, knowledge management, product, design, and engineering teams to optimize processes, improve customer outcomes, and standardize operational planning and reporting.

Lead analytics for Customer Support by owning key metrics, measuring AI and self-service impact, running experiments and causal analyses, supporting capacity planning, and translating insights into operational and product decisions. Build and maintain SQL and dbt data models and pipelines, monitor automation quality, evaluate cost and customer outcomes, and communicate persuasive recommendations to senior stakeholders.

Own financial reporting data logic, metrics, pipelines, orchestration, and validation. Integrate internal data platforms with Anaplan, Planful, and the General Ledger; build audit-ready data extracts and source-of-truth queries; and partner with Finance leadership to ensure accurate, consistent financial disclosures. The role requires advanced SQL and quantitative data skills, basic financial statement literacy, autonomy, and the ability to improve reporting systems and processes.

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.

Generate actionable insights supporting company and customer decisions through curated datasets, metrics, statistical modeling, and deep-dive analysis. Analyze growth drivers, customer segments and cohorts, and the financial impact of marketing and product initiatives. The role requires strong SQL, quantitative analysis, data visualization, stakeholder management, and the ability to influence business direction.

Leads complex, large-scale analytics projects using SQL and Python, oversees BI and reporting delivery, and translates complex requirements into strategic recommendations. Manages and develops 3–4 senior data analysts through coaching, performance management, and technical guidance. The role also establishes analytical standards, engages senior clients, identifies new opportunities, supports practice growth, and explores practical applications of AI and emerging analytics techniques.

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.

Analyze clinical registry data for NHS and private healthcare reporting. Responsibilities include maintaining reporting pipelines, extracting and cleansing data, writing SQL queries, performing analysis and visualization, conducting quality assurance, documenting processes, managing version-controlled changes, and communicating findings to stakeholders. The role requires proficiency in R, SQL, and Excel, with desirable experience in healthcare data, statistical methods, Power BI, Snowflake, data warehouses, and version control.

Analyze, cleanse, transform, and govern business data from property management and financial systems. Build Power BI dashboards, reports, structured datasets, semantic models, and reusable query logic. Use SQL, Python, DAX, Excel, and Microsoft Fabric to identify trends and anomalies, improve reporting efficiency, and deliver actionable recommendations. Collaborate with stakeholders across business functions, support data standards and governance, and contribute to scalable analytics solutions.

Analyzes marketing, sales, customer experience, e-commerce, retail, and campaign performance data. Builds scalable BigQuery and Looker Studio dashboards, defines data models and commercial KPIs, measures campaign uplift and halo effects, analyzes customer journeys and content performance, and translates findings into actionable recommendations for cross-functional stakeholders.

Analyze marketing, sales, customer experience, e-commerce, retail, and promotional performance. Build and maintain scalable BigQuery-backed Looker Studio dashboards, define data models and commercial KPIs, measure campaign uplift and halo effects, analyze customer journeys and content performance, and translate findings into actionable recommendations for cross-functional stakeholders.

Analyze publishing and content acquisition data to support digital product decisions. Design business metrics, build analytics products and dashboards, conduct quantitative research, maintain ETL pipelines and data models, and communicate insights to technical and non-technical stakeholders. The role also promotes data literacy and data-driven decision-making across the organization.

Supports the Chief Data and Analytics Officer by identifying operational risks, designing and evaluating controls, managing control issues and remediation, coordinating audits, supporting regulatory engagements, and overseeing governance and reporting. The role presents updates to senior management, collaborates with control managers, and helps establish best practices for data, AI/ML, and finance control environments.

Investigate and resolve production alerts, improve operational runbooks, validate financial data, identify data-quality trends, and reduce operational risk. The role uses Linux, SQL, scripting, logs, databases, file systems, and workflow tools while collaborating with engineers, analysts, and business partners supporting global trading operations.

Analyze reader engagement and content performance to provide insights for newsroom strategy and business decisions. The role involves interpreting editorial and audience data, communicating findings to varied audiences, collaborating with Product and Engineering on features and experiments, and following data privacy and governance standards.

Develop investment data strategies, pipelines, databases, and models integrating research and portfolio information. Build AI-enabled applications using LLMs, RAG, semantic search, vector databases, and agent frameworks. Create dashboards and tools for investment professionals, prototype solutions, collaborate with engineering and investment teams, and transition successful concepts into scalable applications.

Develop and govern EMEA crisis and incident data landscapes, models, dashboards, and reporting. Produce management information, KPIs, KRIs, and resilience metrics for senior forums while ensuring data accuracy, auditability, and regulatory compliance. Support incident and crisis management teams, thematic reviews, maturity assessments, regulatory reporting, and integration with ServiceNow and critical event management platforms.

Analyze internal and external education data for Camden’s Education Commissioning and Inclusion division. Responsibilities include statutory SEN2 returns, calculating education performance indicators, developing dashboards and self-service data products, delivering bespoke analysis for strategic decisions, and collaborating with data engineering and architecture colleagues to develop data infrastructure.

Provides complex investment data management support for enterprise clients and stakeholders. Resolves data integrity issues, performs root cause analysis, oversees specialist activities, and leads process improvements. Supports projects, change initiatives, workflow enhancements, and operational readiness. Serves as a client-facing thought partner, coordinates with internal teams and external data vendors, and applies investment and data management expertise to improve fund oversight and decision-making.

Analyzes HR and workforce data to develop dashboards, reporting, and actionable insights across retention, recruitment, diversity, engagement, and workforce planning. Maintains data quality, supports governance and reporting automation, evaluates people initiatives, and partners with HR and business leaders to inform strategic decisions and organizational change.

Analyze HR and workforce data to identify trends, risks, and opportunities across the employee lifecycle. Develop dashboards, automate reporting, maintain data quality, support governance and audits, and provide actionable insights for retention, recruitment, diversity, engagement, and workforce planning. Partner with HR and business leaders to support strategic decisions, organizational change, and a data-driven people culture.

Analyze and improve actuarial data quality, reliability, governance, and reporting across Pricing, Reserving, and Portfolio Management. Investigate data issues, bugs, and business impacts; support pricing and portfolio reviews; identify data gaps; and provide actionable insights for commercial decisions. The role requires translating complex findings for technical and non-technical stakeholders while partnering with data teams and actuarial functions to improve analytical processes and digital underwriting capabilities.

Drive product insights through data analysis, experimentation, A/B testing, dashboards, and statistical methods. Build robust data models using SQL and Python or R, translate complex findings into recommendations, and communicate effectively with technical and non-technical stakeholders. Support self-service analytics by training product managers, designers, and engineers to query data and build dashboards. Collaborate with UX Research and other insights teams to strengthen data-driven product decisions.

Collects, cleans, analyzes, and models data to support operational, commercial, and product decisions. Maintains data quality, develops dashboards and reports, identifies trends, and presents actionable insights to technical and non-technical stakeholders. Collaborates across business functions on data-driven initiatives and contributes to improved analytical tools, processes, and solutions.