Director, Pipeline Forecasting, Neuroscience

We are looking for a Director, Pipeline Forecasting, Neuroscience to play a critical role within Worldwide Commercial Excellence by independently developing, maintaining, and delivering forecasts for one or more therapeutic areas.

• Forecasting & Insight Integration
  • Independently lead the end‑to‑end forecasting process for assigned Neuroscience brands, delivering accurate, objective output grounded in transparent assumptions.
  • Integrate insights from market research, competitive intelligence, and chart audits to strengthen assumptions and contextualize forecast outcomes.
  • Support short‑term (1‑ and 3‑year) and long‑range (10‑year) forecasting cycles with structured, analytically rigorous projections.
  • Translate complex business questions into structured forecasting analyses and scenario plans.
• Advanced Analytics & AI‑First Forecasting
  • Develop, maintain, and execute AI‑first forecasting models (Excel‑based, algorithmic, or data‑enabled), ensuring calibration, documentation, and alignment with enterprise standards.
  • Conduct scenario analyses and sensitivity assessments to highlight drivers of uncertainty and enable strategic discussions.
  • Provide feedback to Forecasting Transformation, Data Science, and BI&T teams to improve forecasting logic, data pipelines, and assumption structures.
  • Ensure consistency in forecasting logic across therapeutic areas and planning cycles to support broader enterprise alignment.
• Cross‑Functional Alignment
  • Partner with Finance, MAx, Commercial, Pricing, Medical, and Worldwide teams to align assumptions and ensure a unified forecasting narrative.
  • Participate in cross‑functional reviews to explain forecast drivers, risks, and opportunities, providing an unbiased point of view.
  • Ensure forecasts reflect real‑time market dynamics, competitive signals, customer behavior, access changes, and operational considerations.
  • Support enterprise planning cycles (P‑cycles, Budget, LTFP) by providing timely and accurate inputs.
• Operational Excellence & Governance
  • Maintain rigorous quality control across datasets, assumptions, model logic, and outputs.
  • Ensure transparency, audit readiness, and reproducibility of forecasting deliverables through strong documentation and consistent structure.
  • Identify opportunities to streamline tools, templates, and processes to enhance clarity and efficiency.
  • Support adherence to standardized forecasting practices and enterprise model‑risk guidelines.
• AI‑First Capability Support
  • Partner with Data Science, BI&T, and Forecasting Transformation teams to assist with model calibration, testing of new model components, and alignment with existing methodologies.
  • Contribute to capability building by sharing best practices, structured approaches, and high‑quality forecasting principles with peers.
• Leadership & Collaboration
  • Provide informal mentorship and day‑to‑day guidance to analysts and senior analysts, supporting capability development within the forecasting community.
  • Model structured thinking, data integrity, intellectual curiosity, and an enterprise‑minded approach to decision support.
  • Foster strong collaborative relationships and contribute to a culture of transparency, innovation, and continuous improvement.

• 8+ years of experience in pharmaceutical forecasting, commercial analytics, or related quantitative fields.
• Bachelor’s degree required.
• Proficiency in forecasting methodologies, scenario modeling, and use of pharmaceutical secondary data (e.g., IQVIA, Symphony).
• Experience developing or using Excel‑based, algorithmic, or AI‑enabled forecast models.
• Familiarity with Python or comparable analytical tools to support model calibration or analytical enhancements (preferred, not required).
• Strong ability to synthesize complex data into clear, actionable insights.
• Excellent communication and data‑storytelling skills, with the ability to present clearly to cross‑functional partners.
• Ability to operate in a dynamic environment, manage ambiguity, and apply structured problem‑solving.
• Demonstrated commitment to rigorous quality control, model accuracy, and methodological transparency.
• Intellectual curiosity, adaptability, and enthusiasm for embedding AI‑first thinking into forecasting capabilities.

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