Director - Program Management - Medical Affairs

About the role

The Opportunity: Saama is seeking an experienced Medical Affairs Subject Matter Expert and Program Manager to lead a strategic Evidence Generation product line. This role combines deep Medical Affairs and post-marketing evidence-generation expertise with hands-on program leadership.

Key Responsibilities

• Serve as Saama's principal domain expert for Medical Affairs, Evidence Generation, and post-marketing studies.
• Provide expertise across investigator-initiated trials, research collaborations, non-interventional studies, observational research, Phase IV studies, and related evidence-generation activities.
• Advise on integrated evidence plans, study definitions, portfolio prioritization, scientific-review workflows, operational milestones, and performance indicators.
• Facilitate workshops with scientific, medical, operational, data, and technology stakeholders to identify pain points and define future-state workflows.
• Translate Medical Affairs objectives into clear business requirements, user journeys, decision frameworks, and measurable outcomes.
• Maintain a good understanding of how Scientific Review Committees (SRCs) evaluate investigator proposals.
• Own the engagement roadmap, scope, work plan, milestones, deliverables, dependencies, resourcing, and governance cadence.
• Develop and maintain phased implementation plans covering initial priorities and subsequent expansion opportunities.
• Carefully coordinate activities across Client and Saama teams, including Medical Affairs, Evidence Generation, Data and AI, Client's Digital & Architecture, Security, Compliance, Quality, Product, Engineering, and Implementation services.
• Establish clear roles and responsibilities for data sourcing, preparation, validation, maintenance, and solution operations.
• Manage risks, assumptions, issues, decisions, and change requests, with timely escalation and mitigation.
• Lead executive status reporting, steering-committee discussions, working sessions, and decision reviews.
• Manage client expectations and ensure delivery commitments remain aligned with scope, resources, timelines, and acceptance criteria.
• Support commercial, procurement, and statement-of-work discussions as domain and delivery input is required.
• Lead requirements definition for data ingestion, including structured and unstructured Medical Affairs and evidence-generation sources.
• Partner with technical teams to define data-quality expectations, metadata models, refresh processes, lineage, ownership, and governance controls.
• Guide the design of AI-enabled capabilities supporting study assessment, scientific merit evaluation, strategic alignment, risk stratification, portfolio analytics, and operational decision-making.
• Help define scoring frameworks, business rules, prompts, human-review steps, and traceability requirements.
• Establish measurable evaluation criteria for AI agents and analytical outputs, including accuracy, relevance, consistency, explainability, and usability.
• Ensure appropriate safeguards distinguish descriptive insights from prescriptive recommendations and reduce unsupported or hallucinated outputs.
• Lead or support prototype reviews, user acceptance testing, validation, release readiness, and post-deployment performance monitoring.
• Ensure changing Medical Affairs strategies, evaluation criteria, and operating models can be incorporated through a controlled enhancement process.
• Act as a trusted advisor to senior Medical Affairs, Evidence Generation, technology, and data stakeholders.
• Communicate complex scientific, operational, data, and AI concepts in clear business language.
• Build alignment across client executives, functional leaders, subject-matter experts, architects, engineers, data scientists, and delivery teams.
• Conduct solution demonstrations, roadmap presentations, process reviews, and user-feedback sessions.
• Develop or oversee operating procedures, process documentation, user guides, training materials, and adoption plans.
• Identify opportunities to expand the solution to additional studies, therapeutic areas, or clinical-development use cases based on demonstrated value.
• Maintain operational familiarity with ClinOps workflows across non-interventional studies, prospective registry studies, and Investigator-Initiated Studies.

Qualifications

• Bachelor's or master's degree in life sciences, pharmacy, medicine, public health, epidemiology, clinical research, healthcare, or a related discipline.
• An advanced scientific or clinical degree is preferred.
• 15+ years of experience in the pharmaceutical, biotechnology, CRO, healthcare consulting, or life-sciences technology industry.
• Significant experience in Medical Affairs, Evidence Generation, Real-World Evidence, post-marketing research, or late-phase clinical studies.
• Demonstrated understanding of investigator-initiated trials, research collaborations, non-interventional studies, observational studies, and Phase IV programs.
• Proven experience leading complex, cross-functional programs for a global pharmaceutical organization.
• Ability to convert scientific and operational objectives into requirements, roadmaps, workflows, and acceptance criteria.
• Experience managing senior client stakeholders, delivery risks, dependencies, governance forums, and executive communications.
• Working knowledge of life-sciences data platforms, analytics, data integration, data quality, and visualization.
• Understanding of regulated-system expectations, including GxP principles, data integrity, auditability, privacy, security, and applicable AI-governance requirements.
• Excellent written, verbal, facilitation, presentation, and stakeholder-management skills.

Preferred Experience

• Delivering AI, machine-learning, or generative-AI-enabled solutions in Medical Affairs or clinical research.
• Experience with integrated evidence planning, evidence portfolio management, study feasibility, or scientific proposal assessment.
• Familiarity with real-world data, external research databases, clinical-study metadata, and unstructured-document extraction.
• Experience establishing validation approaches, human-in-the-loop controls, model monitoring, and explainability standards for AI solutions.
• Background in life-sciences consulting, professional services, product implementation, or client solution delivery.
• Experience with Agile delivery and tools such as Jira and Confluence.
• PMP, PgMP, Agile, SAFe, or comparable program-management certification.
• Experience working with globally distributed teams and willingness to travel to client locations as required.