Associate Principal & COAA Scientific AI Lead - Patient-Centered Solutions - UK and EU

About the job

This role is available in the UK and in the European Union. The list of countries in the job ad is not exhaustive.

About us

IQVIA provides scientific services spanning clinical trials, real world evidence, and consulting in all areas of the product lifecycle. Our Clinical Outcomes Assessments (COAs) organisation leads the industry in generating data to ensure that the patient voice is incorporated into the development and commercialisation of medication and other drug/non-drug interventions. We focus on understanding and meeting the needs of our clients – mostly life science/pharmaceutical companies – through the application of broad consulting expertise and technical scientific knowledge to conduct scientifically rigorous research. This research is broad and includes qualitative, quantitative, and passive approaches to understand patient, caregiver, and healthcare professional experiences and expectations of disease and treatment.

The COA Accelerator ecosystem is expanding its AI-enabled product capabilities to help internal teams and external clients develop evidence-backed COA strategies more efficiently, consistently, and transparently. These capabilities are intended to support workflows such as therapy area and indication review, COA instrument selection, endpoint strategy, regulatory precedent assessment, psychometric evidence review, source-backed rationale development, expert review, and report generation.

To meet our client expectations and retain the excellent reputation built up over time, the IQVIA COAs team is committed to recruiting, training and supporting driven individuals who have life science, consulting, product management, AI product, and/or clinical technology skills that can be applied to COA research and technology-enabled offerings. Individuals joining us are assured of a rewarding and progressive career in patient-focused research.

You’ll have the opportunity to address challenging client issues, across multiple geographies, with a hands-on influence in developing and delivering innovative solutions. We operate in a truly multi-cultural, collegial and collaborative work environment that is rich in development and growth.

Role & Responsibilities

• Own the product vision, roadmap, prioritisation, and lifecycle management for AI-enabled COA selection and COA Accelerator capabilities.
• Translate the strategic concepts into practical product capabilities, user journeys, workflows, release milestones, and measurable success criteria.
• Define the product’s target users, use cases, workflows, outputs, quality standards, adoption needs, and commercial value proposition across internal and external use cases.
• Prioritise product capabilities across AI strategy generation, evidence retrieval, source citation, COA recommendation, endpoint selection, assessment schedule design, regulatory considerations, expert review, and report generation.
• Work with COA scientists, HEOR experts, strategy consultants, study teams, sponsors, commercial stakeholders, and clients to understand how COA selection is currently performed and where AI-enabled workflows can add value.
• Map current-state workflows for COA selection, internal expert support, prior-study benchmarking, regulatory precedent review, endpoint recommendation, and client-facing deliverables.
• Define product requirements for user inputs such as therapy area, indication, target product profile, mechanism of action, study phase, target population, endpoint objectives, geography, regulatory pathway, and intended use.
• Define expected product outputs, including recommended COAs, endpoint hierarchy, assessment schedule, rationale, evidence gaps, regulatory considerations, payer considerations, and source-backed recommendations.
• Ensure product requirements are specific enough for engineering delivery while preserving the nuance needed for expert scientific judgement.
• Partner with AI engineers and COA experts to define quality criteria for AI-generated outputs, including factuality, retrieval relevance, citation accuracy, clinical usefulness, consistency, and escalation triggers.
• Define when AI outputs can be used for internal decision support, when they require expert review, and when they may be suitable for client-facing use.
• Create workflows for expert review, feedback capture, error analysis, model improvement, quality monitoring, and continuous product refinement.
• Ensure the product clearly distinguishes between evidence-backed recommendations, expert inference, precedent-based assumptions, and areas of uncertainty.
• Partner with data engineering and domain experts to prioritise the knowledge sources required to power the product, including COA libraries, instrument metadata, psychometrics, clinical trial records, labels, HTA documents, regulatory correspondence, scientific literature, and internal consulting assets.
• Define metadata, traceability, citation, and source inspection requirements from a product and user perspective.
• Serve as a product-facing point of contact for internal stakeholders and selected client-facing discussions related to COA Strategy AI capabilities.
• Support demos, prototypes, pilots, business cases, training materials, internal enablement, onboarding workflows, and adoption planning.
• Work with Commercial and Strategy teams to define product positioning, packaging, differentiation, value story, and integration with broader COA Accelerator.
• Lead cross-functional delivery across AI Engineering, Data Engineering, Software Engineering, COA Science, UX, Security, Legal, Compliance, Commercial, and client-facing teams.
• Own backlog prioritisation, requirements definition, sprint planning input, acceptance criteria, release readiness, stakeholder communication, and product decision documentation.

Skills & Qualifications