Top Data Analyst Jobs in Glasgow

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 transactional data to detect and prevent financial crime, manage AML alerts, build SQL-based models and dashboards, and improve transaction monitoring and customer risk-rating controls. The role owns financial crime operations capacity planning, models scenarios, identifies data-led improvements, and presents insights to business leaders while collaborating with Product, Compliance, and cross-functional stakeholders.

Own GTM and sales analytics across pipeline performance, forecasting, funnel conversion, win/loss analysis, lead and account scoring, territory planning, quota modeling, and capacity planning. Partner with RevOps, Sales, Product, Finance, and Analytics Engineering to improve metric definitions, Salesforce and product data models, dashboards, and decision-making. Translate complex analysis into clear recommendations for GTM leadership.

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 Staff Data Analyst will own trusted metrics for conversion, contracted volume, sales, margins, pipeline, and forecasting. Responsibilities include improving forecast accuracy, diagnosing CRM and transactional data quality issues, analyzing commercial opportunities and partner performance, identifying risks and trends, and translating complex findings into recommendations for senior stakeholders. The role also promotes metric adoption and self-service analytics 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.

Deliver training and communications that improve colleagues’ data literacy and adoption of data products. Create accessible content, facilitate demonstrations and champion communities, analyze user statistics to measure tool uptake, and support the Data Culture Manager with change projects. The role also collaborates with the Microsoft Power Platform team to automate processes and promote effective data-driven decision-making across the organization.

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.

Analyze and integrate multiple data sources, build conformed data models, and create accessible Power BI dashboards and reports. Apply statistical techniques including regression, correlation, and significance testing to generate actionable insights. Clean and transform data using SQL, Python, Power Query, and M, while communicating findings to technical and non-technical stakeholders and recommending emerging visualization technologies.

Delivers data governance initiatives by gathering requirements, documenting processes and data flows, supporting Microsoft Purview adoption, and improving data quality. Works with data owners, stewards, technical teams, and senior stakeholders to define governance processes, metadata standards, business glossaries, ownership models, controls, and quality metrics. Facilitates workshops, translates business needs into requirements and user stories, investigates data issues using SQL and profiling outputs, and communicates risks, dependencies, and decisions.

Investigate and improve the quality of chartering datasets covering vessels, ownership, fixtures, cargo orders, positions, and shipping zones. Use SQL and Python to analyze large datasets, identify inconsistencies, develop validation checks, and investigate root causes. Review AI-parsed fixture data, maintain geographic mappings in QGIS, establish data-quality metrics, and collaborate with Product, Data, Research, Engineering, and AI/ML teams to drive systematic improvements.

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.

The Market Data Analyst will oversee data quality and operations for metals and minerals, monitor market trends, support clients, and improve data workflows using SQL and Python.

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.

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 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.