below marketmost similar roles pay hereabove market
This role pays less than
62%
of similar roles. Most pay
$186,331–$270,243
— the blue band above.
At the midpoint, this role pays about
$205k
versus about
$228k
for comparable roles.
Based on 240 similar postings.
Employer
About AbbVie
AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.
AbbVie currently has
127 open roles
on FindRole.
Listed pay typically runs
$109,500–$208,500
across 119 roles with salary data.
As Associate Director, Global AI Forecasting, you will join the Global Forecasting Center of Excellence to lead the operation, expansion, and governance of AI and machine learning models. You will manage the maintenance of forecasting models to ensure accuracy and reliability while setting technical standards for data requirements, feature engineering, and model selection. Your daily work involves partnering with finance, technology, and brand leaders to translate complex model results into clear business explanations and integrating approved changes into operational workflows. You will utilize Python and R to build production-grade models, including time-series forecasting and ensemble methods. The role focuses on solving commercial volume forecasting problems across various brands and geographies, specifically evaluating emerging approaches like large language models and generative AI for responsible business use.
Lead the operation and maintenance of AI/ML forecasting models to ensure accuracy and reliability for commercial volume forecasting.
Deliver model outputs on schedule to support financial planning cycles and downstream business deadlines.
Define and maintain technical standards for model development, including data requirements, feature engineering, and validation protocols.
Translate complex model results into clear business explanations for non-technical leaders and stakeholders.
Identify and prioritize brands and geographies where AI-enabled forecasting provides the highest value and scalability.
Evaluate emerging AI methods, such as large language models and generative AI, for responsible business use.
Contribute technical expertise to model governance, including documentation standards and monitoring processes.
Lead, coach, and develop a team of forecasting data science professionals by setting priorities and building technical capability.
What we're looking for
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 depth in machine learning model development, validation, deployment, and 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.
Experience leading technical teams or workstreams and delivering high-quality results across multiple concurrent priorities in a complex, matrixed environment.
Ability to translate business context into modeling decisions and communicate technical outputs clearly to non-technical audiences and senior leaders.
Experience in pharmaceutical, biotech, or life sciences commercial analytics, forecasting, or data science (preferred).
Experience with commercial volume forecasting, pharmaceutical data sources, and integrating AI/ML models into operational business processes (preferred).
Machine Learning
Python
R
Time-series Forecasting
Supervised Learning
Ensemble Methods
Generative AI
Large Language Models
Feature Engineering
Model Governance
Data Science
Production ML
Statistics
Python
PyTorch
TensorFlow
Generative AI
Large Language Models
LangChain
LangGraph
Semantic Kernel
AWS
Microsoft Azure
Langfuse
Retrieval-Augmented Generation
Git
Microservices
APIs
Natural Language Processing
Deep Learning
Generative AI
Machine Learning
MLOps
Python
R
Scala
Java
AWS
Azure
Databricks
Causal Inference
Optimization
Predictive Modeling
Model Governance
Data Science
Statistics
Econometrics
Operations Research