Director/Senior Director - Program Management - Medical affairs
Location: Remote / client-facing; NJ preferred
Department: Life Sciences Services
Employment Type: Full-time
About Saama
Saama focuses on the specialized needs of pharmaceutical and biotechnology companies, delivering transformative business outcomes through AI, advanced analytics, deep life-sciences expertise, and collaborative solution development. Our teams work with global life-sciences organizations to solve complex clinical, medical, and commercial challenges using data-driven and AI-enabled solutions.
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. The successful candidate will act as the primary bridge between Client stakeholders and Saama’s services, product, data engineering, data science, and AI teams.
The individual will help shape and deliver an AI-enabled operational and decision-support platform spanning investigator-initiated trials, research collaborations, non-interventional studies, and post-marketing/Phase IV studies. The role requires someone who can translate scientific and operational needs into an executable roadmap while maintaining rigorous governance, validation, and stakeholder alignment.
Key Responsibilities
Medical Affairs and Evidence Generation Leadership
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.
Ensure the solution supports scientifically credible, transparent, and decision-grade outputs.
Good understanding of how Scientific Review Committees (SRCs) evaluate investigator proposal.
Program and Engagement Management
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.
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.
Data, Analytics, and AI Solution Delivery
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.
Stakeholder Engagement and Adoption
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.
Operational familiarity with ClinOps workflows across non-interventional studies, prospective registry studies and Investigator Initiated Studies
Qualifications
Required
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.
Success Measures
The successful candidate will:
Establish an agreed engagement roadmap, governance structure, delivery plan, and responsibility model.
Create alignment between Medical Affairs priorities and the technical solution.
Deliver clear, approved requirements and scientifically sound acceptance criteria.
Maintain predictable execution with transparent management of scope, risks, dependencies, and decisions.
Ensure AI and analytical outputs are validated, traceable, governed, and appropriate for business use.
Drive stakeholder confidence, user adoption, and measurable operational value.
Identify responsible expansion opportunities across additional evidence-generation and clinical-development use cases.
Key Competencies
Deep life-sciences domain expertise
Client leadership and trusted-advisor presence
Program ownership and execution discipline
Scientific and analytical problem-solving
Clear executive and technical communication
Cross-functional collaboration and influence
Comfort operating in ambiguity
Strong judgment, integrity, and accountability
Innovation balanced with quality and governance
Why Join Saama?
Help shape an important AI-enabled Medical Affairs and Evidence Generation transformation.
Work directly with senior stakeholders at a leading global pharmaceutical organization.
Combine scientific domain expertise with advanced data, analytics, and AI capabilities.
Collaborate with multidisciplinary teams across product, engineering, data science, and life-sciences services.
Make a measurable contribution to evidence-based decision-making and patient outcomes.
Saama is an equal opportunity employer. Responsibilities may evolve based on engagement requirements and business priorities.
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