Director, Market Access Operations & Analytics

Key Responsibilities

• Partner with Market Access, Commercial Operations, Finance, Tech, and Data teams to turn pain points into clear, specific problem statements.
• Identify where AI and agentic technology can create the most value across pricing, contracting, channel management, trade operations, and payer engagement — weighing impact, feasibility, and risk to prioritize investment.
• Build business cases with clear expected benefits, costs, and success measures; shape the AI roadmap, balancing quick wins with long-term capability, and assess build, buy, and partner options.
• Own delivery end to end - leading data scientists, engineers, UX designers, and vendors through design, build, evaluation, and production deployment, making key build and release decisions tied back to the business case.
• Partner with Data Engineering and commercial data owners to secure the data foundation these products depend on - contract, pricing, rebate, claims, and channel data quality, lineage, and master data alignment.
• Set the quality bar for AI solutions - validate before release, then own them after go-live: monitor model, prompt, and agent performance in production, manage versioning and change control, triage failure cases and drift, and run continuous improvement loops from user feedback.
• Ensure responsible AI use, with human oversight, documentation, compliance, and governance built in from the start.
• Manage budgets, timelines, vendor performance, and delivery risk, flagging issues early.
• Prototype and validate solutions in the real world, then drive adoption - enablement, training, documentation, and SOP updates - and convert proven solutions into reusable patterns other Commercial and D&T teams can adopt.

Basic Qualifications

• 10+ years in life sciences or healthcare, with experience in market access commercial operations - account management, pricing, contracting, channel management, trade operations, or payer engagement.
• Bachelor's degree in business, economics, data science, computer science, public health, or life sciences.
• Experience translating complex business problems into programs that deliver measurable results.
• Experience setting priorities and building roadmaps or investment cases that senior leaders acted on.
• Experience overseeing technology delivery from design through production deployment, ideally including AI or advanced analytics.
• Experience managing delivery teams and vendors - budgets, timelines, quality - on complex programs.
• Hands-on experience building and operating agentic AI or LLM-based workflows in production - not just pilots - from idea to measured outcome.
• Experience with agile delivery and testing/validation in regulated environments.
• Technical knowledge to engage data scientists and vendors on model and agentic workflow evaluation, monitoring, and governance.
• Experience building trusted relationships with senior stakeholders and explaining complex ideas clearly.

Preferred Qualifications

• Advanced degree (MBA, MSc, MPH, PhD) in a relevant discipline.
• Direct experience building AI solutions for market access operations, real-world evidence, or health technology assessment.
• Experience designing or operating agentic AI/automation platforms (e.g., LLM orchestration frameworks, workflow or agent builders) in a regulated enterprise setting.
• Familiarity with cloud AI platforms (Azure AI, Google Cloud, AWS) and MLOps/LLMOps concepts.
• Experience with human-in-the-loop systems, prompt engineering, or deploying generative AI in regulated environments.
• Experience assessing AI vendors or platforms.
• Experience leading transformation, merger integration, or operating model change.