Product Manager, Clinical Development Platforms

Core Product Management Responsibilities

• Define and maintain product vision, strategy, roadmap, and success metrics.
• Partner with business stakeholders to identify opportunities, pain points, and desired business outcomes.
• Conduct discovery activities, including stakeholder interviews, workflow analysis, current-state and future-state assessments, and end-to-end understanding of users, personas, journeys, pain points, and desired outcomes.
• Partner with UX/Design to translate discovery insights into detailed journey maps, service-experience designs, prototypes, and usability validation.
• Develop product roadmaps based on business value, strategic priorities, risk, complexity, dependencies, and resource constraints.
• Lead prioritization of product capabilities, features, enhancements, and enabling investments.
• Create and maintain business cases and value hypotheses for product investments.
• Assess market and technology trends, vendor solutions, and build-versus-buy opportunities.
• Establish product success measures and track adoption, value realization, user satisfaction, and operational impact.
• Translate business needs into clear product requirements, workflows, use cases, business rules, and acceptance criteria.
• Ensure requirements are complete, testable, traceable, and ready for development.
• Facilitate product decisions, prioritization, and scope tradeoffs across stakeholders.
• Define product boundaries and identify business, workflow, system, integration, and data dependencies.
• Apply systems thinking to understand how users, decisions, workflows, information, and products interact across the clinical-development ecosystem.
• Collaborate with technical teams to evaluate solution options and make informed product decisions.
• Participate in backlog refinement, release planning, roadmap reviews, and product governance checkpoints.
• Ensure alignment between business objectives, approved scope, and delivered product capabilities.
• Support products throughout discovery, workflow analysis, validation, design, development, release, adoption, support, and continuous improvement.
• Own product vision, roadmap, prioritization, requirements quality, acceptance criteria, stakeholder alignment, release-scope definition, and measurable outcomes.
• Partner with business stakeholders on adoption, change management, communications, training, and value realization.
• Establish structured mechanisms for post-release feedback, support intake, backlog triage, and product learning.
• Monitor product performance and identify opportunities to improve outcomes and user experience.
• Facilitate release readiness with business, quality, delivery, and technical teams.
• Maintain alignment and communicate product decisions throughout planning and delivery.
• Establish clear product decision rights, including who recommends, contributes, approves, is informed, and serves as the escalation authority.
• Identify and manage product risks, assumptions, business dependencies, and cross-product impacts.
• Partner with Technical Leads and Architects on solution options, feasibility, non-functional requirements, technical dependencies, and risks.
• Partner with Project, Program, or Delivery Management on integrated plans, schedules, RAID management, release coordination, and cross-team follow-through.
• Influence cross-functional teams without formal authority and communicate effectively with business and executive stakeholders.
• Produce fit-for-purpose product artifacts, including discovery summaries, stakeholder maps, workflows, use cases, PRDs, roadmaps, decision logs, dependency maps, release scope, and product metrics.
• Identify opportunities to use AI, including generative and agentic AI, automation, analytics, and decision intelligence to improve user outcomes and productivity.
• Define AI use cases, intended use, human-in-the-loop workflows, business requirements, user controls, evaluation criteria, measurable outcomes, and adoption needs for AI-enabled features.
• Collaborate with Data Science, AI, Engineering, Architecture, Quality, and domain experts to deliver responsible and measurable AI capabilities.
• Define expected outputs, validation approaches, quality criteria, representative test scenarios, and human review expectations.
• Use AI-assisted methods to accelerate discovery synthesis, requirements critique, workflow analysis, prototyping, and identification of gaps.

Clinical Development Domain Responsibilities

• Develop a strong understanding of clinical development, clinical operations, regulatory, safety, data management, medical writing, and related business processes relevant to the assigned product portfolio.
• Partner with R&D stakeholders to understand clinical workflows, operating models, user needs, decision points, data needs, and compliance expectations.
• Translate complex clinical, scientific, and operational processes into scalable digital-product capabilities.
• Collaborate across functions to improve process efficiency, quality, compliance, traceability, and user experience across the clinical development lifecycle.
• Support digital transformation initiatives that improve planning, execution, oversight, documentation, and decision-making.
• Understand clinical information and logical data flows at a product level, including what information is needed, where it originates, who consumes it, the decisions it supports, and the upstream/downstream impact of change.
• Apply appropriate product controls for regulated or validated solutions, including auditability, role-based access, data integrity, testing evidence, and controlled release expectations.

Preferred Domain Focus: Protocol Authoring and Workflow Automation

Experience in one or more of the following areas is highly desirable but is not required across every area:

• Clinical protocol authoring or digital protocol solutions
• Study design platforms and Schedule of Activities
• Clinical document management or medical writing platforms
• CRF design, clinical data collection, or study setup automation
• Protocol amendments, version management, comparison, lineage, or change-impact assessment
• Workflow automation, structured content, traceability, or metadata management
• AI-assisted content authoring, document intelligence, extraction, or review
• Clinical-trial technology ecosystems and interconnected downstream workflows