Company Description

About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

AbbVie’s Global Forecasting Center of Excellence sets forecasting standards and builds the analytical capabilities that guide enterprise planning. As Associate Director, AI Forecasting, you will lead the operation, expansion, and governance of AI and machine learning models used to forecast commercial volume across brands and geographies. You will set technical standards, guide model development and deployment, and partner with forecasting, finance, technology, and business leaders to keep model outputs reliable, explainable, scalable, and aligned with planning cycles.

Responsibilities

• Lead the operation and maintenance of AI/ML forecasting models, ensuring their ongoing accuracy, reliability, performance, and fitness for use in commercial forecasting.

• Ensure model outputs are delivered on schedule to support financial planning cycles and downstream business deadlines.

• Define and maintain standards for developing new forecasting models, including data requirements, feature engineering, model selection, validation, documentation, integration, and handoff.

• Partner with forecasters, brand teams, finance leaders, and technology teams to understand business dynamics, curate inputs, determine when model changes are warranted, and integrate approved changes into operational workflows.

• Translate complex or counterintuitive model results into clear, well-supported business explanations that help leaders understand and confidently use model outputs.

• Identify and prioritize the brands and geographies where AI-enabled forecasting can create the greatest value, balancing quality, scalability, and delivery timelines across concurrent workstreams.

• Serve as a technical leader for AI/ML methods applied to commercial forecasting, evaluating emerging approaches, including large language models and generative AI, for responsible business use.

• Contribute technical expertise to model governance, including documentation standards, validation protocols, monitoring, review processes, and responsible-use guidelines.

• Lead, coach, and develop a team of forecasting data science professionals, setting priorities, allocating work, providing feedback, and building technical capability as the modeling portfolio grows.

Qualifications

Required

• Bachelor’s degree in a quantitative field such as Statistics, Data Science, Computer Science, Engineering, or Mathematics (advanced degree strongly preferred).

• 7+ years of progressive experience in quantitative or analytical roles, with demonstrated depth in machine learning model development, validation, deployment, and ongoing operation.

• Expert-level proficiency in machine learning, including time-series forecasting, supervised learning, ensemble methods, and model performance evaluation.

• Proficiency in Python and/or R, with hands-on experience building, deploying, and maintaining production-grade ML models.

• Ability to translate business context into modeling decisions and communicate technical outputs clearly to non-technical audiences and senior leaders.

• Experience leading technical teams or workstreams and delivering high-quality results across multiple concurrent priorities in a complex, matrixed environment.

• Strong documentation, knowledge management, problem-solving, and judgment.

Preferred

• Experience in pharmaceutical, biotech, or life sciences commercial analytics, forecasting, or data science.

• Experience with commercial volume forecasting and pharmaceutical data sources, such as prescription, patient flow, distribution, and epidemiology data.

• Experience integrating AI/ML models into operational business processes with defined planning cycles and downstream dependencies.

• Familiarity with enterprise forecasting platforms and model governance frameworks.

• Experience evaluating large language models, generative AI, or other emerging analytical methods in a business context.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.

• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.

• This job is eligible to participate in our long-term incentive programs.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

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https://www.abbvie.com/join-us/reasonable-accommodations.html