Top Data Analyst Jobs in Glasgow

Supports Finance and Go-To-Market departments by designing data recording systems, monitoring data quality, enforcing governance, analyzing large datasets, producing concise reports, and recommending process improvements. The role translates complex findings into actionable insights for non-technical stakeholders and supports Sales, Marketing, and Customer Success objectives.

Build and enhance AWS QuickSight reporting for Customer Service, create reusable datasets, integrate business data sources, and establish consistent metrics and documentation. The role translates stakeholder needs into dashboards, automates manual reporting, validates data quality, investigates issues, and supports self-service analytics and knowledge transfer during a six-month engagement.

Analyze complex datasets, develop dashboards and reports, translate stakeholder requirements into data-driven solutions, and support analytical models and AI-enabled capabilities. The role involves collaborating with engineers and multidisciplinary Agile teams, ensuring data quality and documentation, presenting insights, and supporting UX/UI design within a secure Defence programme.

Develop and maintain Power BI dashboards, reports, and analytical outputs supporting Fleet operations and PMO decision-making. Analyze operational data covering compliance, utilization, vehicle performance, maintenance, costs, risks, and exceptions. Translate stakeholder needs into reporting, automation, and process improvements; investigate data quality issues; support governance, documentation, integrations, and data flows; and communicate actionable insights to technical and non-technical stakeholders.

Analyze Gecko engine telemetry across desktop and Android to identify data-quality issues, including bot contamination and hardware noise. Build automated dashboards, audit telemetry collection gaps, develop data-sanitization methods, and produce statistical analyses connecting technical performance metrics with user behavior and engagement. Translate complex engineering data into actionable product and budget recommendations for leadership while working independently across Performance, Data, and Product teams.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Analyze campaign and CRM data using SQL and BigQuery, reconcile data sources, investigate discrepancies, and build accurate Power BI dashboards. Present actionable marketing insights and recommendations to stakeholders, explain methodology and limitations, defend findings, and independently make routine analytical decisions while escalating significant blockers.

Collect, clean, validate, and analyze data using Excel, SQL, Power BI, and Microsoft Fabric. Create dashboards, reports, visualizations, KPI reporting, and actionable recommendations for business and client decision-making. Collaborate with analysts, consultants, and stakeholders, present findings clearly, maintain reporting solutions, and support data quality and project delivery. The role offers early-career development in data analytics and consulting.

Embedded within the commercial team, the Senior Data Analyst will own core sales and revenue metrics, improve pipeline and forecast accuracy, investigate CRM data quality, size commercial opportunities, and analyze partner, retention, and renewal performance. The role translates ambiguous business questions into actionable recommendations, defines trusted metric frameworks, communicates insights to senior stakeholders, and increases self-service analytics adoption across non-technical commercial teams.

Own analytics across the participant lifecycle to support acquisition, onboarding, activation, engagement, quality, retention and reactivation. Build metrics, dashboards, and experimentation frameworks with SQL and Python; partner with Product, Operations, Growth, and Data Science to run experiments and translate marketplace data into actionable decisions that improve participant health and supply sustainability.

Leads client data initiatives in an investment banking environment, translating business requirements into functional and data specifications. Defines data mappings, lineage, migration, reconciliation, and master data hierarchies. Queries complex datasets with SQL, validates implementations, enforces data governance, and collaborates with architecture, engineering, and project teams in Agile delivery. Supports client onboarding, KYC, regulatory reporting, reference data, and other capital markets change programs while engaging senior stakeholders.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

Use SQL and Python to analyse transaction monitoring and fraud rule performance, identify patterns and anomalies, reduce false positives, and prioritise high-risk cases. Partner with FinCrime, Product, Compliance and Data teams to improve controls, data pipelines and detection logic, support scoring and future ML use cases, and translate analysis into actionable recommendations that balance fraud prevention with customer friction.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.