Sr. Director, Forecasting Pipeline, Oncology

Position Summary 

The Senior Director, Forecasting, Sr. Director, Pipeline, Oncology, is an enterprise leader within Worldwide Commercial Excellence who sets the strategy, standards, and vision for forecasting across multiple brands and therapeutic areas. This role elevates forecasting as a strategic decision‑support capability by shaping enterprise methodologies and assumptions frameworks, advancing AI‑first forecasting platforms, and ensuring outputs are accurate, transparent, comparable, and decision‑useful across planning horizons. 

The Senior Director partners with senior leaders across Commercial, Finance, MAx, Medical, Pricing, Worldwide/Regional markets, Supply/GPS, and Investor Relations to drive assumption alignment and support portfolio and investment decisions. The role leads a multi‑level team (Analysts through Directors), builds future leadership bench strength, and champions continuous improvement, governance, and audit‑readiness at scale. 

Key Responsibilities 

Enterprise Forecasting Strategy & Leadership 

• Define and steward the enterprise forecasting strategy, standards, and common assumptions frameworks across brands and therapeutic areas. 

• Represent forecasting in senior governance forums (e.g., Commercial LT, Finance LT), articulating integrated performance drivers, risks, and scenario implications to inform enterprise choices. 

• Lead portfolio‑level scenario ecosystems (1‑, 3‑, and 10‑year), ensuring consistent methods, transparent drivers, and comparable outputs for planning, budgeting, LTFP, and strategic reviews. 

• Align forecasting with cross‑functional and global needs, ensuring the right cadence, signal quality, and traceability for enterprise decisions. 

• Act as a visible thought leader, elevating forecasting from numerical outputs to strategic narratives that clarify the ‘so what’ for executive stakeholders. 

Advanced Forecasting, Analytics & AI‑First Innovation 

• Oversee enterprise frameworks for demand, patient flow, and net sales forecasting, including integration of gross demand, GTN, pipeline/inventory, and net sales components in partnership with Finance and MAx. 

• Guide long‑range projections and sensitivity/what‑if constructs that support portfolio strategy, investment trade‑offs, and BD evaluations. 

• Champion an AI‑first forecasting platform—steering modular, scalable model components that reduce manual scenarioing, increase speed and transparency, and maintain methodological rigor. 

• Ensure model governance, validation, and calibration discipline are embedded across use cases and markets, with clear documentation for audit readiness. 

Cross‑Functional Partnership & Enterprise Alignment 

• Drive unified forecasting assumptions with Commercial, Finance, MAx, Medical, Pricing, and Worldwide/Regional stakeholders; coordinate with Supply/GPS and other partners to synchronize operational signals and constraints. 

• Serve as a senior interface to Investor Relations and other enterprise forums when integrated forecasting perspectives are required. 

• Ensure forecasts reflect current market events, access dynamics, competitive actions, policy changes, and customer behavior, with clear translation into strategic implications. 

Platforms, Tools & Capability Building 

• Provide strategic direction for the AI‑first platform roadmap, partnering with Data Science, BI&T, and Forecasting Transformation to deliver fit‑for‑purpose, scalable solutions. 

• Sponsor improvements in data quality, metadata, and pipelines, and codify reusable assets (playbooks, templates, code modules) that improve repeatability and comparability. 

• Establish a community of practice and best‑practice repositories to uplift craftsmanship, documentation rigor, and analytical storytelling across global teams. 

Operational Excellence, Governance & Performance 

• Set the bar for quality control, documentation standards, change control, and audit‑readiness; track compliance to enterprise model‑risk and methodology guidelines. 

• Define and monitor function‑level KPIs/OKRs (e.g., cycle time, variance drivers, forecast accuracy, assumption transparency) to continuously improve impact. 

• Lead resource planning and vendor/partner management, ensuring appropriate capacity and quality for peak planning cycles. 

Leadership, Talent & Organizational Development 

• Lead and develop a multi‑level team (Analysts through Directors), creating clarity of purpose, elevating standards, and ensuring consistent, high‑quality outputs across brands/TAs. 

• Build succession depth and future leadership bench, fostering an inclusive, collaborative culture that values curiosity, structured thinking, and enterprise mindset. 

• Coach leaders on structured problem solving, assumption discipline, executive storytelling, and AI‑first ways of working; model BMS leadership behaviors (integrity, inclusion, urgency, accountability, passion, innovation). 

Qualifications, Skills & Experience 

• 9+ years of experience in pharmaceutical forecasting, commercial analytics, or related quantitative fields; global experience strongly preferred. 

• Bachelor’s degree required; advanced degree preferred (e.g., MBA, MS Analytics, MPH). 

• Demonstrated expertise in forecasting methodologies (demand, patient flow, net sales), long‑range planning, and scenario/sensitivity design at portfolio scale. 

• Proven success leading multi‑level teams and shaping enterprise standards, platforms, and governance. 

• Track record of influencing VP+ stakeholders and senior governance forums with concise, strategic narratives. 

• Experience overseeing AI‑enabled/algorithmic forecasting ecosystems; familiarity with Python or similar analytical languages appropriate to leadership oversight. 

• Strong change‑leadership credentials in capability building, process excellence, and cross‑functional alignment. 

• Exceptional executive communication and data storytelling skills; able to synthesize complex signals into clear, actionable guidance. 

• Enterprise mindset with comfort operating in dynamic, ambiguous environments and across global matrices. 

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