Top Data Jobs in Edinburgh

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, RAG, hybrid search, and agentic workflows. Analyze large-scale intellectual property datasets, design experiments, evaluate and benchmark models, define reasoning strategies, and translate findings into product recommendations. Collaborate with product managers, IP experts, and engineers to deliver scalable, customer-facing solutions.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, generative AI, retrieval, and hybrid search. Define multi-step reasoning workflows, analyze large-scale intellectual property datasets, establish model evaluation and benchmarking practices, and translate experiments into product recommendations. Collaborate with product teams, intellectual property experts, and engineers to deliver scalable, customer-facing solutions.

Lead and grow a Data Science team to deliver end-to-end, scalable ML/AI solutions for online personalisation. Partner with product, engineering and commercial teams to embed models, set standards for agile delivery, testing and model monitoring, and drive innovation to improve customer experiences and business value.

Design, build and maintain scalable, automated cloud data solutions and pipelines. Provide technical leadership to a small engineering squad, own complex backlog tasks, develop data frameworks and standards, and ensure code quality via reviews and pair programming using Databricks, Python, SQL and Spark.

Design and maintain reliable data solutions, lead a squad of engineers, develop scalable data pipelines, and ensure adherence to data standards.

Leads complex machine learning delivery and Defence-sector strategy, translating client challenges into technical roadmaps, scoping projects, managing client relationships, and supporting technical sales. Writes production-grade Python, serves as a machine learning authority, develops Generative AI and agentic AI solutions using LLMs, and mentors and manages data scientists.

Lead and develop a Data Science team to deliver scalable ML/AI solutions for an online Personalisation programme, ensuring impactful customer experiences.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

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.

The Finance Data Manager will analyze complex financial and operational datasets, translate business requirements into scalable data assets, and deliver management reporting and commercial insights. Responsibilities include collaborating on data pipelines, automating financial reporting with code and AI, building reporting solutions, improving processes, and partnering with stakeholders across the business.

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.

Manage HV electrical packages for hyperscale data centre construction across pre-construction, construction, and close-out. Coordinate contractors and owner-direct vendors, support bid and contract processes, track schedule and budget, drive value engineering, and ensure completion of close-out documentation and authority inspections. Significant international travel to Finland and familiarity with local legislation required.

Lead quality management for a large Nordic data centre construction project: develop and deliver the Quality Management Plan, coordinate client and contractor quality teams, manage on-site/off-site testing and Factory Witness Testing, oversee construction documentation via the client EDM system, ensure contract specification compliance, and promote a project-wide quality culture and induction training.

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.

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.

Design, build, and scale cloud-native data warehouses and robust ETL/ELT pipelines (primarily BigQuery). Optimize performance, implement partitioning and cost controls, ensure data governance, observability, and regulatory reporting support, and collaborate with analytics and engineering stakeholders.

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 operate Databricks production data pipelines for a predictive CRM platform: monitoring, incident response, cost and performance optimization, migrating legacy ETL, onboarding customers, enforcing Delta Lake architecture and multi-tenant isolation, and applying CI/CD, security, and observability best practices to ensure reliable, scalable data delivery.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Senior Data Scientist owning end-to-end analytical problems: experiment design, predictive and inferential modeling, performance measurement, and cross-functional partnership to improve retail AI products. Duties include data acquisition, modeling, validation, auditing system outputs, building reusable statistical methods, and communicating findings to influence product and operations.

Data Contributors will research startups, analyze global data for StartupBlink's Global Startup Ecosystem Index, and compile accurate information for publication.

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 role involves developing go-to-market strategies for VAST Data within the UK Defence & Secure Government sectors, building relationships with key stakeholders, identifying and closing strategic sales opportunities, and representing the company at industry events.

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.