Executive Director, CASA, Portfolio & Forecasting AI

Bristol Myers Squibb • Princeton, NJ

7d • $273,870 - $331,866 • Hybrid

About The Position

The Executive Director, CASA, Portfolio & Forecasting AI is responsible for designing, building, and scaling AI-driven forecasting products and decisioning capabilities that power Bristol Myers Squibb’s portfolio planning, brand forecasting, and financial outlook. This role owns the end-to-end AI product roadmap for demand, inventory, and Gross-to-Net (GTN) forecasting—from data ingestion and model development to deployment, monitoring, and closed-loop learning—ensuring accuracy, transparency, and explainability across brands and markets. As a senior leader within the AI & Omnichannel organization, this executive partners closely with Finance, Commercial Operations, Market Access, Supply/Inventory, and BI&T to modernize the forecasting tech stack, embed predictive and generative AI where valuable, and institutionalize governance that meets audit, compliance, and risk standards. The role emphasizes portfolio-level forecasting (scenario planning, sensitivity analysis, multi-brand optimization) and launch readiness forecasting.

Requirements

• 12+ years in pharmaceutical, healthcare, or adjacent industries with deep experience in forecasting, planning, and AI/ML product management.
• Bachelor’s degree required; advanced degree (MS, PhD, MBA) in Data Science, AI, Statistics, Operations Research, Economics, Applied Mathematics, or a related quantitative field strongly preferred.
• Proven track record of leading, developing and deploying AI driven forecasting initiatives at scale with measurable improvements in accuracy, efficiency, and business impact.
• Deep understanding of demand, inventory, and Gross-to-Net (GTN) modeling with familiarity of hybrid planning ecosystems such as GTN in Anaplan with cloud data/analytics
• Experience partnering with Finance, Commercial Operations, Market Access, Supply/Inventory, and BI&T to shape forecasting strategy and portfolio decisions.
• Drive cross-functional leadership across data science, product, ML engineering, and risk teams, leveraging deep expertise in data architecture and MLOps to enable robust model deployment and seamless integration with planning and finance systems
• Advanced proficiency in time-series modeling, hierarchical forecasting, causal inference, simulation/optimization, scenario planning for portfolio management and publishing executive-friendly narratives
• Proficiency with Python, R, SQL, cloud ML platforms, and enterprise BI tools (e.g., Tableau, Power BI) for forecast visualization and variance tracking.
• Strategic agility with a bias for action; balances MVP speed with governance, audit readiness, and long-term scalability.
• Exceptional communication and data storytelling skills; able to translate complex model outputs into actionable insights for senior stakeholders.
• Demonstrated ability to influence senior leaders, drive enterprise change, and foster a culture of innovation, rigor, and transparency.
• Experience managing vendor/partner relationships, including data sources, planning platforms, and model ops tools.

Nice To Haves

• Strategic Collaborator: Trusted advisor to senior executives, bridging insights, strategy, and execution.
• Customer-First Mindset: Champions understanding and serving customers across all engagement touchpoints.
• Enterprise Leader: Balances BU-specific needs with broader enterprise priorities and capabilities.
• Innovative Thinker: Anticipates future trends and applies new tools and technologies to strengthen engagement.
• Empowering Collaborator: Builds high-performing teams and develops future leaders across the organization.

Responsibilities

• Define and own the multi-year product strategy for AI-enabled forecasting (Demand, Inventory, GTN), with clear business outcomes, KPIs, and adoption milestones.
• Align the roadmap to enterprise planning cycles, therapeutic area launch timelines, and AI & Omnichannel priorities; maintain a portfolio lens across brands and markets.
• Quantify value (accuracy lift, cycle time reduction, transparency) and prioritize investments (models, data, tooling, MLOps) accordingly.
• Manage and co-own AI forecasting products (modules, services, APIs) across Gross Demand, Inventory Management, GTN transformation—including archetypes, features, guardrails, and refresh cadences.
• Translate business requirements into product backlogs, release plans, and SLAs; ensure explainability and diagnostics are first-class features.
• Govern model lifecycle (development, validation, approval, deployment, monitoring, retraining) with BI&T and Finance; establish champion–challenger testing and drift detection.
• Partner with BI&T to secure the right pipelines and platforms (cloud data warehouse/lake, semantic layers, feature stores, orchestration) for scalable forecasting AI.
• Enforce interoperability with planning tools, inventory inputs, and enterprise reporting layers; design APIs for downstream consumption.
• Establish forecasting model governance: documentation, sign-offs, versioning, audit trails, and regulatory/privacy controls for data and outputs.
• Create business rule frameworks (e.g., demand drivers, GTN rate/mix assumptions, inventory policies) with controlled change management and stakeholder approvals.
• Run risk assessments for key models/processes; implement mitigation strategies for data gaps, drift, and policy changes.
• Lead portfolio-level scenario planning (pricing, payer shifts, policy changes, supply constraints) using AI simulations and sensitivity analysis.
• Deliver explainable AI artifacts (feature importance, stability metrics, back-testing, variance explanations) for executive and Finance stakeholders.
• Institutionalize closed-loop learning—link forecasts, actuals, and adjustments to improve models and business rules over time.
• Serve as the single point of accountability for forecasting AI with Finance, Commercial Operations, Market Access, Supply/Inventory, BI&A, BI&T, and TA leaders.
• Drive adoption via training, playbooks, office hours, and executive readouts; publish recurring forecast quality dashboards and action-oriented commentary.
• Build and lead a high-performing forecasting AI cross-matrix team (product managers, data scientists, ML engineers, model risk) across HQ and offshore; set a culture of rigor, transparency, and impact.
• Manage vendors/partners (data sources, planning platforms, model ops tools); enforce SLAs and value realization.

Benefits

• Health Coverage: Medical, pharmacy, dental, and vision care.
• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Work-life benefits include: Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
• Based on eligibility, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
• All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive