Top Data Analyst Jobs in London

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.

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.

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.

Own end-to-end analytical projects: scope business problems, build Looker dashboards and Hex notebooks, write production-quality SQL and Python, monitor KPIs, diagnose data discrepancies, communicate insights to stakeholders, and use AI/LLMs to accelerate analysis while ensuring accuracy and repeatability.

Own pricing model and P&L analysis for Wise Platform: investigate cost data, propose pricing and cost improvements, monitor financial performance, improve pricing model and liaise with subject matter experts to surface actionable insights that drive profitability and growth.

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.

The Associate Data Analyst collaborates to create data products and visuals, ensures data accuracy, and handles ad-hoc requests while contributing to team projects.

The Associate Data Analyst will deliver insights dashboards and data products, ensure data accuracy, and handle ad-hoc requests while collaborating with team members and stakeholders.

The Data Analyst delivers insights and data products, collaborates with teams, creates dashboards, and supports operations through ad-hoc requests.

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.

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.

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.

The Platform Data Analyst will enhance visibility and performance optimization of Runware's media AI platform through analytics, monitoring, and reporting. Responsibilities include tracking performance, building dashboards, and collaborating with engineering and DevOps teams to improve observability and reliability.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.

Entry-level data analyst role working with survey and platform data to produce cleaned datasets, weighted analyses, visualisations, and partner-facing reports. Use SQL (BigQuery), Python (pandas/numpy), and plotting tools; maintain notebooks, survey instruments, and documentation; collaborate with engineering to improve pipelines. Six-month proving ground with potential for permanent hire.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Analyze marketing campaign performance, provide insights on acquisition, LTV, attribution, engagement and retention; support segmentation and targeting; run A/B tests; build automated data pipelines and dashboards; collaborate with product, engineering and marketing teams and act as the data point of contact for marketing.

Build and maintain automated data collection pipelines, clean and model Gas and LNG datasets, produce analyses and visualisations to support trading, collaborate with data scientists and traders, and deploy/operate data products with strong data governance.

Perform data profiling and analysis, build and maintain visualisations and dashboards, define KPIs and a performance management framework, present actionable insights, lead stakeholder workshops, and collaborate with agile delivery teams to support decision-making.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Lead end-to-end SAP data migration for large S/4HANA programs: analyze legacy and target models, define mappings, perform profiling and cleansing, build migration datasets with SAP tools, develop reusable frameworks and automation, create data quality dashboards, support cutover and post-go-live stabilization, and mentor data teams.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

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.

Develop and maintain shared Power BI semantic models and dashboards using star schema. Write SQL against BigQuery, optimize report performance, define data/reporting best practices with Microsoft Fabric integrations, and consult on wireframes and visualizations to deliver actionable marketing insights for stakeholders.

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.