Top Data Jobs in Bristol

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.

Support migration and content/catalogue data workstreams: develop data quality frameworks, build Power BI reports, perform SQL-based transformations, validate and reconcile data, document data flows, and liaise with stakeholders to ensure accurate migrations and catalogue integrations.

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.

Lead a team building Owkin's agentic AI Scientist for drug discovery by applying multimodal omics and ML to discover targets, biomarkers, and disease subtypes; collaborate with biologists, engineers, and partners; shape platform capabilities, publish results, and grow a high-performing research team.

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.

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.

Design and validate end-to-end data platform solutions (ingestion, transformation, storage, semantic layers, consumption) that embed governance, security and non-functional controls. Translate business outcomes into data product definitions, provide design assurance during delivery, contribute reference architectures and patterns, and coach teams to ensure consistent, resilient, and scalable delivery for BI, analytics and operational use cases.

Lead complex data analysis and source-system investigations to define, validate and document data requirements. Translate requirements into measurable business outcomes and technical specifications, ensure end-to-end traceability, apply data governance, lead data quality assessments, and collaborate with data engineering and senior stakeholders to deliver sustainable data products.

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.

Lead and deliver data insight products (reports, dashboards, visualisations), gather requirements via workshops, analyse data across descriptive to prescriptive analytics, advise stakeholders on effort and technical implications, and manage, coach, and develop a small analytics team.

Analyse membership and CRM data to produce insights that inform engagement and membership strategy. Source and manipulate data from multiple systems, run statistical analyses, deliver regular and ad-hoc reports, create visualisations, present findings to technical and non-technical stakeholders, and contribute to cross-functional projects to improve member outcomes.

Hands-on, client-facing senior data analyst who profiles and investigates large production datasets, diagnoses anomalies, sizes risk, guides data engineers, shapes requirements with stakeholders, and presents actionable insights while navigating governance for sensitive data.