[Hiring] Director/Senior Director - Program Management @Apptad, Inc.

Role Description

We are 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 client'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 & Evidence Generation Leadership
  • Serve as client'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.
  • Maintain a good understanding of how Scientific Review Committees (SRCs) evaluate investigator proposals.
• Program & 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 client 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 & 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 & 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.
  • 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.

Success Measures & Competencies

• 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.

Education

• Bachelors or Master's degree in Computer Science, Information Technology or relevant field.