Top Data Analyst Jobs in Edinburgh

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.

Maintain and transform investment data by building data systems and pipelines, performing complex analysis, combining multiple sources, improving data quality, and presenting results via visualization. Collaborate with clients, system architects, and product teams to deliver actionable insights and analytical tools for data-driven decisions.

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.

Analyze player behavior and live-game performance across retention, engagement, progression, funnels, cohorts, churn, and monetization. Build dashboards, define KPIs, investigate anomalies, and communicate insights clearly. Own the internal game analytics platform, ensuring reliable event tracking, consistent metric definitions, and accessible performance views. Collaborate with developers and potentially help transform the platform into a public Roblox analytics product.

The Data Analyst develops and maintains Power BI and Tableau reports, monitors data pipelines and refresh schedules, ensures data quality, and supports business-critical planning and reporting processes. The role interprets data, communicates insights, trains users, supports data governance and literacy initiatives, coordinates reporting activities, and works with stakeholders and IT Services on system improvements, cloud migration, and report deployment. Responsibilities also include workload prioritisation, documentation, regulatory data submissions, and community-of-practice activities.

Develop and maintain enterprise Power BI and Tableau reporting solutions, data pipelines, models, dashboards, and analytics using Snowflake, SQL, dbt, and Alteryx. Analyze institutional and external data to support strategic planning, forecasting, recruitment targets, and executive decision-making. Ensure data quality, reporting governance, release standards, and stakeholder satisfaction. Provide technical guidance, training, and support across the University, contribute to emerging AI-enabled analytics, and potentially line-manage junior developers.

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.

Owns data quality, reporting, analytics, and deal-management data for a private companies investment team. Builds and improves Power BI dashboards, reconciles investment and financial data across systems, identifies insights and risks, and supports decision-making. The role also manages data models, reporting processes, transaction records, and continuous improvement initiatives across platforms including iLevel and Snowflake. It requires strong stakeholder collaboration, financial data analysis, and practical automation and AI exploration.

Supports implementation and operation of data governance frameworks within asset management. Responsibilities include maintaining data dictionaries and glossaries, developing data quality validation rules, reporting governance metrics, identifying and resolving data quality gaps, strengthening controls, coordinating governance forums, and translating data governance requirements for delivery teams. The role partners with data owners, stewards, technology teams, and operational stakeholders to improve data quality and mitigate risk.

Conduct fundamental credit research, assess capital structures and investment risk, and support security selection and portfolio construction. Use Python, SQL, AI, and analytical tools to improve research, monitoring, idea generation, and investment workflows. Collaborate with portfolio managers, analysts, and firm-wide teams to implement practical solutions, communicate research clearly, and contribute to evolving the Income team’s investment process.

Manages compliance surveillance technology, data, and automation supporting second-line risk assurance. Performs alert and case reviews, control testing, system configuration, data analysis, and trend identification across investment, compliance, business risk, and financial crime areas. Translates assurance requirements into dashboards, queries, workflows, and continuous monitoring capabilities while validating AI and automation outputs, improving data quality, and reporting system performance and assurance findings to 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.

Owns the integration and analysis of people, security, technology, fraud, physical security, investigation, and governance data to identify insider-risk patterns. The role produces actionable intelligence, supports investigations, strengthens controls, and develops monitoring, automation, governance, and reporting capabilities. It requires influencing senior stakeholders, translating complex findings into business outcomes, and making risk-based recommendations amid ambiguity.

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.

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.

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 develop the company’s Power BI reporting environment, including semantic models, dashboards, advanced DAX, Power Query transformations, governance, deployment, and performance optimization. Collaborate with Data Engineering and business stakeholders to define KPIs, validate data, improve reporting quality, and deliver scalable BI solutions. Support data architecture, data quality, ad hoc analysis, and continuous improvement across enterprise reporting assets.

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.

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.

Support implementation of data governance frameworks across Pensions & Savings. Work with Data Owners, Stewards, and Risk to monitor data quality, track governance actions, maintain documentation, and produce regular and ad-hoc reports to support regulatory compliance and governance maturity. Contribute to continuous improvement of data governance processes and stakeholder reporting.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.