Top Data Jobs in Edinburgh

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.

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.

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.

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

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 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.

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 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 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.

Design, build and optimise scalable cloud-native data platforms and pipelines using Microsoft Fabric, Azure Databricks, Synapse and ADF. Implement ETL/ELT with PySpark and SQL, ensure data governance, performance, reliability, and collaborate with data scientists and engineers to deliver production solutions.

Lead data strategy and standards across product teams, develop experimentation best practices, mentor data scientists and analytics engineers, collaborate with product/engineering/design/research, and apply advanced data techniques to improve user engagement and product decision-making.

The Forward Deployed Data Solution Engineer works embedded within teams to ensure software quality, guide technical decisions, and design integration patterns, focusing on AI-enabled capabilities and data governance.

Manage the full commercial lifecycle for enterprise and strategic customer accounts: renewals, pricing, contract amendments, upsell strategy, and expansion. Build bespoke commercial strategies using usage data and market context, forecast renewal pipeline, lead commercial QBRs, negotiate with senior stakeholders and procurement, and partner with Customer Success and solution consultants to quantify ROI and drive retained and expanded ARR.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Support ledger migration and data lake cleanup by extracting, transforming, reconciling and validating large datasets. Develop and validate SQL queries, batch jobs and processing logic, perform regression testing, document mappings and validation rules, and collaborate with engineering, product and business teams to ensure production readiness and post-migration validation.

Design, build, and maintain scalable cloud-based data platform and ETL pipelines on Azure. Develop data models, ensure data quality, optimize performance, implement governance and security, and collaborate with stakeholders and data scientists to enable data-driven solutions.

As a Senior Data Scientist, you'll develop AI solutions with machine learning, mentor others, and ensure responsible AI practices while collaborating with clients to solve business challenges.