Top Data Jobs in Edinburgh

Lead design and delivery of production-grade AI/ML solutions for Kainos Workday products. Build predictive analytics, anomaly detection, generative AI features, and scalable MLOps pipelines. Integrate with Workday, mentor and line-manage a data science team, manage client engagements, and drive architectural and technical leadership across product initiatives.

Support delivery of AI/ML solutions for Workday products by applying statistical and machine learning methods, building models and visualisations, assisting deployment alongside engineers, and collaborating with senior team members to learn and deliver on client projects.

Design and deliver production-grade AI/ML solutions for Kainos Workday products, including LLM-driven features, model deployment, dashboards, and mentoring junior staff. Collaborate with engineering and clients to improve product functionality, scalability, and efficiency.

Abstract and enter clinical data from health records, ensure data quality and confidentiality, use EHR/practice management systems and Microsoft Office, troubleshoot basic access/VPN/MFA issues, and collaborate with clinical teams to support operations.

Define and build quality frameworks for human data programs, partner with clients and engineering to design evaluation, recruitment and annotation strategies, implement automated checks and dashboards, investigate data integrity, and upskill teams to deliver high-quality human data at scale.

Lead design and delivery of a deterministic identity graph and graph-driven identity intelligence. Discover features from connected data, build link-analysis pipelines, prototype identity-resolution and fraud/risk models, define quality signals and ingestion workflows, align data capabilities with product goals, select graph technologies, document standards, and mentor/grow a data science team while shipping production-grade graph-enabled product features.

Lead multi-skilled agile teams to design, build and productionise modern data solutions. Own technical architecture, collaborate with infrastructure and customer architects, define functional and non-functional designs, mentor staff, estimate delivery timelines, contribute to data community and support pre-sales technical solutioning.

Design and deliver scalable Customer Data Platform solutions (Oracle Unity), build and operate data pipelines and Customer 360 models, integrate CDP with data lake/CRM/marketing systems, lead architecture and data modelling workshops, ensure data quality, governance, security, and support CDP operations, and partner with Oracle implementation teams.

Lead design and implementation of scalable generative AI services and reusable components using Python. Drive architectural decisions, deploy containerized applications on Kubernetes (EKS), ensure scalability/observability and CI/CD, mentor engineers, and collaborate with product and research teams to productionize LLM capabilities.

Work with stakeholders, product and technical teams to elicit, document, and translate business and data requirements into user stories and acceptance criteria. Support backlog refinement, run workshops, assist data analysis and validation, and identify process improvements to enable data-driven decisions.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

The Solution Architect will design and implement big data solutions for overseas clients, requiring expertise in various big data technologies and cloud services, as well as strong communication and technical presentation skills.

Hunt and close net-new enterprise accounts across the UK for a data/AI infrastructure platform. Own full sales cycle from pipeline generation to close, engage technical and economic buyers, partner with pre-sales and channel, manage forecasting and deal negotiations, and represent VAST at industry events.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Design, build, and deploy production-ready ML models emphasizing recommendation and ranking systems. Apply NLP and behavioural analytics to large-scale datasets using Databricks and Spark. Run experiments (A/B tests), monitor and optimise live models, and collaborate with engineers and product teams to deliver measurable business impact.

Lead and mentor a Data Engineering team to design, build, and optimize scalable Microsoft-based data platforms (Fabric, Databricks, Synapse, Azure). Develop PySpark/Spark SQL pipelines, orchestrate with ADF/Synapse/Fabric Pipelines, manage Azure DevOps and CI/CD, scope tasks, review code, and drive Agile delivery while acting as technical SME and stakeholder partner.

Lead global workforce planning and people analytics, building supply/demand models, scenario planning, dashboards, and predictive models. Partner with HR, Finance and segment leaders to align headcount, support restructuring and cost optimisation, ensure data governance and compliance, and present executive-ready workforce insights.

Lead data architecture and strategy across OLTP, OLAP, and AI systems. Drive AI-first foundations (LLM orchestration, RAG, real-time inference), ensure DataOps/CI-CD, mentor technical leads, run architectural reviews, partner with product and engineering leadership, and optimise platform security, observability and costs.

As a Data Engineer, you will design, build, and maintain data pipelines and infrastructure to support data-driven decision-making in a collaborative environment.

Develop, fine-tune, evaluate, and productionise ML and LLM models for customer feedback tasks (extraction, retrieval, reranking, summarisation, sentiment). Build retrieval and embedding pipelines, contribute to evaluation frameworks and metrics, write tested code, collaborate on integrations and monitoring, and translate product needs into ML experiments while keeping up with research.

As an Energy Consultant, you'll bridge Gorilla's SaaS solutions with energy market needs, drive pre-sales engagements, and support deal strategies through workshops and tailored presentations.

Lead the Finance & Regulatory Data team, overseeing finance data strategy, governance, and analytics to support corporate finance and audits.

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.

The Data Mentor provides technical support and feedback to apprentices, ensuring high standards in teaching, learning, assessment, and learner progression monitoring.

As the Data Engineering Manager, you'll lead a team, manage data infrastructure, design scalable solutions, and drive data quality initiatives while collaborating with cross-functional teams.