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.

Act as a strategic partner to electric utility customers, defining 3-5 year IT/OT architecture roadmaps, advising on ADMS/EMS/SCADA/GIS/DMS/OMS and cloud, data, integration and cybersecurity considerations, facilitating senior workshops, supporting early project design, and building long-term customer relationships while developing reusable consulting methods.

Lead large-scale transformation programmes across strategy, delivery, digital and data to drive customer-focused, sustainable energy solutions. Partner with senior leaders to align investment, governance and workforce capability, embed cultural change, and deliver measurable business benefits using automation, analytics and AI.

Support portfolio risk models by ensuring input and derived data are accurate, validated, and well-governed. Design QC rules, prototype validation logic, onboard new datasets, monitor data quality, and coordinate cross-functional resolution with modeling, engineering, and upstream data teams. Communicate risks and lead data governance initiatives for global fixed income and equity modeling.

Lead and scale multi-team AI engineering and data science organization to design, deliver, and govern GenAI, LLM, Vision AI, and multi-agent knowledge products; own end-to-end solution design, Agile delivery, quality standards, production validation, stakeholder alignment, hiring, and organizational capability building.

The Sales Lead drives revenue growth through strategic account development in Energy, Financial Services, and Public Sector, leading a sales team and shaping transformation offerings.

Lead clinical trial disclosure strategy and operations for Pfizer-sponsored interventional trials. Ensure timely, compliant posting of protocols, SAPs, CSRs, and clinical summaries per EMA Policy 70 and other regulations. Manage vendors, develop processes and technical solutions, represent Medical Writing on governance committees, and maintain regulatory knowledge and best practices to drive quality and consistency across disclosures.

The Data & AI Portfolio Lead drives the development and integration of Fujitsu's Data & AI portfolio in the UK, aligning with strategic objectives and managing offerings throughout their lifecycle while providing leadership to product managers.

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.

Lead the development and execution of the NA digital transformation and data strategy, enhancing capabilities in AI and digital technologies across the business.

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.

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.

Design, build, and validate complex EDC (Medidata Rave) databases per protocol. Create eCRF packages, program edit checks and custom functions, configure integrations (IWRS, Safety Gateway, Datamart), perform migrations, train junior staff, and support process and tool improvements within clinical data management.

Provide timely, risk-based legal advice on data protection, FOIA, PECR and NIS matters; manage caseloads; ensure legally accurate ICO guidance; represent ICO externally; supervise and develop legal staff; liaise with external counsel and internal stakeholders.

Design and deliver an integrated AI and data upskilling programme: create scenario-based, role-specific learning, embed training into technology adoption, define tool readiness, pilot cohorts, evaluate behavioural and process outcomes, and align stakeholders to enable safe, applied AI and data use at scale.

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 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.

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.

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 improvements to external market data and act as product owner for the National Storage Mechanism. Drive data quality, modelling and technology change, coordinate cross-team projects, build medium-term transparency plans, gather user feedback, and support Market Oversight initiatives to improve effectiveness through better use of data and technology.

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.

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 the data platform product to enable experimentation, production ML, AI-assisted analytics, data quality, automation for data engineering, scalable delivery, governance, and measurable business impact across product and data teams.

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.

Deliver HR data, insights and reporting across the employee lifecycle. Produce regular and ad-hoc reports and dashboards, ensure data governance and accuracy, support reward analytics including gender pay gap and pay review modelling, maintain HRIS reporting, and present findings to stakeholders to inform decision-making.