Senior Associate, Data Science and AI

About the job

The Global Commercial Analytics (GCA) team within the Chief Marketing Office (CMO) organization is dedicated to transforming data into actionable intelligence, enabling the business to remain competitive and innovative in a data-driven world. We play a pivotal role in extracting insights from large and complex datasets to drive strategic decision-making. Collaborating closely with various subject matter experts across various fields, our team leverages advanced statistical analysis, machine learning techniques, and data visualization tools to uncover patterns, trends, and correlations within the data. Additionally, we are dedicated to delivering new, innovative capabilities by deploying cutting-edge Machine learning algorithms and artificial intelligence techniques to solve complex problems and create value. We are looking for a Senior Associate, Data Science and AI who will be responsible for delivering data-derived insights and/or AI-powered analytics tools to Pfizer’s Commercial organization and will support a brand or therapeutic area. This includes leading the execution and interpretation of AI/ML models, framing problems, and shaping solutions with clear and compelling communication of data-driven insights. We are seeking a hands-on Data Scientist to design and implement advanced analytics and machine learning solutions that drive commercial decision-making in the pharmaceutical domain. The ideal candidate will have strong expertise in statistical modeling, forecasting, segmentation, clustering, classification, and regression, with experience in Bayesian methods. Familiarity with pharma or healthcare data is highly desirable. Exposure to agentic AI frameworks is a plus. This role is dynamic, fast-paced, highly collaborative, and covers a broad range of strategic topics that are critical to our business. Key Responsibilities - Predictive Modeling & Forecasting - Develop and deploy forecasting models for sales, demand, and market performance using advanced statistical and ML techniques. - Apply Bayesian modeling for uncertainty quantification and scenario planning. Segmentation & Targeting - Implement customer/physician segmentation using clustering algorithms and behavioral data. - Build classification models to predict engagement, conversion, and prescribing patterns. Commercial Analytics - Design and execute regression models to measure promotional effectiveness and ROI. - Support marketing mix modeling (MMM) and resource allocation strategies. Machine Learning & AI - Develop ML pipelines for classification, clustering, and recommendation systems. - Explore agentic AI approaches for workflow automation and decision support (good-to-have). Data Management & Visualization - Work with large-scale pharma datasets (e.g., IQVIA, Veeva CRM, claims, prescription data). - Create interactive dashboards and visualizations using Tableau/Power BI for senior stakeholders. Collaboration & Communication - Partner with Commercial, Marketing, and Insights teams to understand business needs. - Present analytical findings and actionable recommendations through clear storytelling.

Requirements

• Statistical Modeling
• Forecasting
• Clustering
• Classification
• Bayesian Methods
• Data Visualization

Qualifications

• Master’s or Ph.D. in Data Science
• Statistics
• Computer Science
• related quantitative field

Preferred Technologies

• Statistical Modeling
• Forecasting
• Clustering
• Classification
• Bayesian Methods
• Data Visualization

About the company

The Global Commercial Analytics (GCA) team within the Chief Marketing Office (CMO) organization is dedicated to transforming data into actionable intelligence, enabling the business to remain competitive and innovative in a data-driven world.