Top Data Jobs in Edinburgh

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.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

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.

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

Lead or contribute to statistical programming for clinical trials, focusing on SDTM/ADaM datasets and TLFs. Oversee quality, validation, and dataset specifications, communicate with sponsors, and provide guidance on programming requirements. Oncology experience and team leadership are advantageous.

The AI Account Executive will manage sales cycles, build a self-sourced pipeline in AI, and engage with C-level executives to close new deals.

Manage clinical data activities for trials: design CRFs and databases, program/test edit checks, perform coding (MedDRA/WHO‑Drug), export CDISC SDTM datasets, generate queries, coordinate data entry and DB developers, support database lock and sponsor communication.

The role involves owning product feature development, participating in system design, and maintaining software performance in an agile setting.

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

As a Data Scientist, you will design and deploy data-driven fraud prevention solutions, working directly with clients to tackle unique challenges. You'll build machine learning models and collaborate with engineering to enhance backend systems.

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.

Measure and optimize underwriting using statistical analysis and machine learning on claims, risk signals, and underwriting data. Build models for risk assessment, pricing, and automation; create dashboards and reports; collaborate with actuarial, product, and engineering teams; lead initiatives and mentor team members to improve underwriting efficiency and risk selection.

The Director Analyst focuses on data integration and engineering, providing insights, advice, and research to help organizations improve their data practices and strategies.

Lead single-threaded product and technical ownership for Client Intelligence & Data, defining APIs and event-driven architectures to deliver merchant-facing analytics, KPIs, and reports. Drive platform strategy toward AI-driven insights, enforce production reliability and automated QA, champion You Build It You Run It culture, partner cross-functionally to scale multi-tenant analytics capabilities, and prioritize work using evidence-based frameworks.

The Data Engineer will design and support data warehouses, create analytics dashboards, perform data quality analysis, and identify process improvements. Responsibilities include collaborating with stakeholders to develop insights and ensure data governance.

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

As a Senior Data Engineer, you will design and develop large-scale data processing software, manage technical components, and mentor team members, while ensuring code quality and operational readiness.

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.

Lead ownership of private markets data model and architecture, manage integration/connector inventories, design data migration and integration frameworks, advise clients and support sales, and bridge advisory and technical delivery teams to enable BI and enterprise performance solutions.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.