Top Data Jobs in Edinburgh

The Cyber Security Data Operations Engineer will develop and manage data analytics applications, design solutions, and ensure effective documentation and user support for cyber security data processes.

Lead development of a modern first-line technology control environment, embedding automated, preventative and real-time controls across cloud-native platforms. Partner with Technology, Data and AI teams to support resilience, cloud migration and platform transformation. Use data-driven monitoring to improve control effectiveness, influence senior leaders, and build a high-performing Control Office team.

Lead research and architect GenAI solutions for cybersecurity, design and implement LLM and deep learning models, drive training and deployment at scale, mentor scientists, establish evaluation frameworks, and represent technical leadership through publications and cross-functional collaboration.

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.

As a Product Manager at Bringg, you will define product strategy, work with stakeholders, manage the roadmap, and integrate AI into logistics solutions.

Lead and deliver data-driven audit analytics: design scalable automated control tests, acquire and analyze large datasets, visualize findings, enable auditor self-service, train staff, and advance the global Audit Data Analytics program while ensuring compliance with data and technology standards.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

As the Director of Data Science, you'll mentor teams, oversee projects, drive data-driven decisions, and implement AI and ML solutions while enhancing our data pipeline.

Partner with Digital X Technology, Data & AI leaders to ensure investment decisions deliver value and financial control. Oversee P&L and balance sheet impacts, support strategic planning, appraise transformation initiatives (cloud, platform modernisation), lead a finance team, and provide executive-level financial insight and escalation in a regulated banking environment.

Lead applied AI research and architecture for GenAI in cybersecurity: design LLM architectures, implement production-grade deep learning systems at scale, mentor scientists, set technical standards, and align AI strategy with business goals.

The Fraud Analyst role focuses on investigating fraud cases, collaborating with teams to improve fraud detection, and refining operational processes while ensuring data quality and participant experience.

Lead a team of data scientists to build and maintain data pipelines, clean and transform data, develop statistical and machine learning models, deliver predictive analytics, and partner with stakeholders to drive business value and governance.

Support clinical data management by maintaining eCRFs and validation specs, reconciling clinical and third‑party data, tracking study metrics, addressing data queries, and identifying root causes to resolve data issues while collaborating with project teams.

Design, build, maintain, test and optimize scalable data architectures and pipelines. Extract, transform and load data for analysts and scientists, ensure data quality, collaborate with architecture teams, adopt DevOps practices, and source/integrate new data to support bank products and cost-effective platform solutions.

Perform asset data audits for defence projects: validate legacy and project data using the LISA geospatial system, assign barcodes, affix labels, prepare and submit audit reports, liaise with teams, conduct site visits, and maintain records for quality assurance.

Perform asset data verification and audits for defence projects using internal geospatial system LISA. Validate Master Site Plans and Land Management plans, assign barcodes, affix labels, prepare and submit audit reports, liaise with internal teams, maintain audit records, and conduct site visits including multi-day rural travel.

Manage and maintain spatial data and related documentation for Defence estate assets. Ensure data accuracy, integrity and accessibility, oversee estate barcode label application, maintain O&M and fire evacuation manuals, manage drawing files and information repositories, and support spatial planning and compliance across multiple bases.

The Data Scientist (Product Analytics) will develop product analytics, improve data quality, conduct A/B tests, analyze user behavior, and collaborate with cross-functional teams to inform product strategies and enhance user engagement.

Lead a specialist BPA data team to manage end-to-end pension scheme data for buy-in/buy-out transitions. Ensure data accuracy, validation, reconciliations, benefit specification oversight, governance, regulatory compliance, stakeholder integration, third-party data management, and drive automation and continuous improvement to support successful scheme migrations.

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.

Lead and shape the Security Data & AI Lab's data engineering capability: define strategy and roadmap, own scalable cloud-native data pipelines and platforms, embed secure-by-design and engineering best practices (CI/CD, testing, observability), enable production-grade foundations for AI/ML, mentor engineers, and partner across Security, Cloud, Architecture and Product teams.

Lead a team of data scientists to design and deliver ML/AI solutions for cyber threat detection and prevention. Develop anomaly detection, time-series and deep learning models, deploy LLM-based security automation (RAG, prompt engineering, fine-tuning), and build production ML pipelines with Data Engineers on GCP. Ensure explainability, ethics, and regulatory alignment while translating insights for cyber defence, risk, and compliance stakeholders.

The Data Assistant will perform research and data collection on power plants, supporting the Power and Renewables team with data management and quality improvement.

Lead and grow a data engineering squad to build reliable, scalable data platforms and pipelines supporting experiments, real-time experiences and AI/ML use cases. Drive engineering excellence, delivery, observability, CI/CD, and cross-functional collaboration with product, analytics and data science.

Support design, development and maintenance of data product pipelines for regulatory security monitoring and compliance. Assist with data ingestion, telemetry, automation of control monitoring, and collaborate with engineers and security specialists while learning modern engineering practices.