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 and maintain clients' asset and reference data, validate investment data, manage data providers, mentor analysts, collaborate on reference data strategy, and ensure compliance with procedures and risk controls.

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

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.

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.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Own commercial growth for a strategically important enterprise account: build executive relationships, execute multi-year account plans, win new business, translate technical propositions into commercial cases, manage account marketing and governance, maintain pipeline and forecasting, and coordinate local GTM teams to drive predictable revenue growth.

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.

The Enterprise Account Executive will drive new enterprise revenue, engage with senior decision-makers, and execute growth strategies for Data and AI training solutions.

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.

As an Engineering Manager, oversee data engineering and analytics projects, while leading teams focused on data platforms and governance. Foster collaboration and ensure operational compliance.

Lead Data Engineers will build data platforms, create data lakes and warehouses, and transform data into integrated models while leading teams and advising clients.

The Senior Data Engineer will lead teams in building data platforms and pipelines for clients, focusing on data integration and analytics solutions using various technologies.

Advance analytics and ML solutions for a global pharma client: develop, implement and monitor models; build data models and BI analyses (Spotfire); liaise with stakeholders; improve provisioning and inspection-ready documentation; apply statistical methods to solve business use cases.

Design, build, and maintain production-grade data pipelines, Python services, and Databricks workloads for a large-scale financial data platform. Improve performance, reliability, observability, and data models; troubleshoot issues; participate in architecture, code review, and cross-team collaboration to deliver enterprise reporting and integrations.

Lead and grow a data science team to design, develop, evaluate, and deploy production-grade AI/ML solutions (LLMs, Generative AI, RAG, transformers). Own technical vision, MLOps/LLMOps, model governance, and cross-functional execution with Product and Engineering to deliver scalable business impact in financial markets.

Lead definition, monitoring and reporting of Group financial crime KRIs and tolerances. Drive data quality, investigations and MI for AML, sanctions, fraud and CDD. Partner with technology and business units to maintain data infrastructure, implement automated reporting, enhance controls and deliver dashboards and governance across the organisation.

The Software Engineer will develop data pipelines, manage cloud infrastructure, and collaborate with AI scientists to enhance data acquisition for model training.

On-site mechanical quality coordinator for a large data centre construction project: oversee mechanical construction, review and approve ITPs and checklists, verify works against standards, develop QA/QC checklists in BIM, witness commissioning (HVAC, pumps, piping, fire protection), ensure contractors complete BIM 360 records, verify calibration and as-built/red-line accuracy, escalate and drive resolution of quality issues, and promote continual improvement.

Implement, audit and troubleshoot GA4 and Google Tag Manager setups, manage conversion tracking across major ad platforms, maintain server-side tracking, diagnose data quality issues, and build client-facing reports and dashboards. Handle ad-hoc tickets and client-facing delivery across DTC and B2B eCommerce accounts.

Lead commercial management, governance and optimisation of market data services across the organisation. Manage supplier relationships, contracts, licensing, inventory and usage controls, drive cost optimisation, ensure compliance, partner with Investment, Finance, Procurement and Change teams, and shape market data strategy and operating model.

Perform setup, installation, calibration, operation, troubleshooting and documentation of analog and digital instrumentation and data acquisition/processing systems. Assist with data interpretation, customer communication, and multi-skill development while working assigned rotating shifts.

Define, set up and ingest external clinical data streams (labs, ECG, imaging, EHR, wearables, genomics). Plan set-up activities, create trial-specific Data Transfer Agreements, translate medical concepts into data mappings, perform UAT, implement transfers into the CDR, monitor data quality and resolve provider conformance issues while ensuring regulatory and data protection compliance.