Senior COA Scientist, Scoring & Interpretation

Senior COA Scientist, Scoring and Interpretation About the role

This role serves as a scientific lead for the interpretation, documentation, and governance of Clinical Outcome Assessment (COA) scoring algorithms. The position is responsible for translating complex source materials—including scoring manuals, publications, and author guidance—into scientifically robust, implementation-ready requirements, while resolving ambiguity in scoring logic, missing-data handling, and interpretation.

Acting as the critical bridge between COA source documentation and downstream statistical, product, engineering, and operational teams, the role ensures scoring methodologies are accurately implemented, clinically meaningful, and aligned with validated instrument standards.

The role also contributes to strengthening IQVIA’s scoring capability by developing reusable scientific assets, standardised documentation practices, and governance frameworks that enable consistent, high-quality deployment of scoring solutions across delivery models and technologies.

Role & Responsibilities
• Provide scientific leadership across COA evaluation and implementation, applying expertise in measure development, instrument documentation, scoring methodology, and interpretation to ensure outputs are scientifically robust and fit for clinical research use.
• Contribute to high-quality COA science across the organisation by supporting methodological best practices, reviewing scientific deliverables, collaborating with cross-functional teams, and strengthening scalable processes for both instrument-related and scoring-related work
• Interpret scoring manuals, instrument documentation, publications, and related source materials to define scientifically valid, implementation-ready scoring requirements, including score structures, derivations, recoding, transformations, weighting, conditional logic, among others.
• Define and document missing-data handling rules, minimum completion thresholds, suppression logic, and other algorithm requirements where source guidance is incomplete, ambiguous, or complex.
• Assess and document interpretation guidance associated with COA scores, including severity bands, score meaning, benchmarks, and other clinically relevant interpretation outputs where supported.
• Identify, evaluate, and resolve ambiguities in scoring methodology, escalating appropriately when scientific judgement, author clarification, or senior SME input is required.
• Partner with statisticians, programmers, product, and engineering teams to translate scientific requirements into validated scoring implementations.
• Investigate discrepancies, implausible outputs, and scoring-related issues to determine root cause and support robust resolution.
• Serve as the scientific point of contact for internal queries related to scoring logic, interpretation, algorithm complexity, and implementation feasibility.
• Contribute to standard templates, SOPs, review checklists, and reusable scientific assets that improve the quality, consistency, and scalability of scoring operations.

Required Qualifications - our ideal candidate will have
• Advanced degree (PhD, MSc, MPH, PharmD, psychology, outcomes research, public health, psychometrics, epidemiology, health sciences, or related discipline).
• Minimum 7 years of relevant experience in COA science, outcomes research, psychometrics, patient-centred research, or closely related scientific roles within pharma, CRO, healthcare research, or instrument development.
• Experience with instrument development, validation, psychometric evidence, or interpretation / meaningful-change work.
• Deep familiarity with COA concepts, including domains, scoring structures, recall periods, missing-data rules, interpretation, and fit-for-purpose use in clinical research.
• Strong, demonstrable experience interpreting and applying scoring methodologies for clinical outcome assessments, including at least some experience beyond simple sum or average scoring.
• Demonstrable experience translating scientific source materials into structured documentation, specifications, reports, or implementation guidance.
• Ability to evaluate ambiguous…