Senior Manager, Data Science & Analytics (Media Mix Modelling)

Role Summary

Are you passionate about using data science, AI, and autonomous agents to unlock the return on every marketing dollar? Do you thrive where advanced analytics, agentic AI, and commercial strategy meet? Join our team as a Senior Manager, Marketing ROI Data Science, where you will lead the design, development, and deployment of marketing mix modeling, multi‑touch attribution, and AI‑driven marketing ROI optimization solutions that measurably improve how the business invests across channels.

In this role, you will leverage cutting‑edge technologies—including marketing mix modeling, causal inference, generative AI, and agentic AI systems that plan, execute, and optimize marketing decisions with limited human intervention—to answer the defining question of what actually drives marketing ROI and where the next dollar should go. You will translate spend, media, channel, and outcome data into smarter decisions across brand, commercial, and portfolio teams, work closely with cross‑functional stakeholders, mentor high‑performing analytics teams, and help shape the organization’s marketing analytics and agentic AI roadmap.

The ideal candidate is a strong analytics leader with deep marketing mix / marketing ROI expertise and genuine enthusiasm for agentic AI, comfortable in global, cross‑functional teams and able to bridge data, technology, and commercial strategy to turn analytics into decisions and action.

Role Responsibilities

• Lead the design, development, and deployment of marketing analytics solutions, including cross‑channel attribution, budget optimization, and scenario planning that guide where and how marketing invests.
• Build and scale agentic AI systems for marketing analytics—autonomous and semi‑autonomous agents that ingest data, run models, generate insights, and recommend or execute budget and channel decisions under human oversight.
• Apply machine learning, causal inference, Bayesian methods, and generative AI to quantify marketing effectiveness, isolate incrementality, and continuously improve ROI across brands and channels.
• Act as a thought leader and subject‑matter expert on marketing mix modeling, marketing ROI, and agentic AI, providing strategic guidance to senior commercial, brand, and technology stakeholders.
• Partner with commercial, brand, media, finance, and technology teams to align marketing analytics and AI initiatives with business and portfolio objectives.
• Lead and mentor a team of data scientists and marketing analysts, fostering technical excellence, agentic‑AI fluency, and professional growth.
• Establish and maintain reusable analytics assets and agent frameworks, scalable pipelines, and best‑practice standards (e.g., MLOps, LLMOps and agent orchestration, model governance, and AI lifecycle management).
• Translate complex modeling outputs into clear, decision‑ready marketing ROI narratives for both technical and non‑technical audiences, including senior leadership.
• Stay current with emerging trends in agentic AI, generative AI, marketing measurement, and cloud platforms, proactively identifying opportunities to raise marketing ROI and analytics maturity.
• Contribute to planning, prioritization, and change management for marketing analytics and AI initiatives across multiple stakeholders and markets.

Technical Skills & Competencies

• Strong strategic and analytical mindset with the ability to solve ambiguous marketing and commercial problems using data‑driven, ROI‑focused approaches.
• Hands‑on expertise in marketing mix modeling, multi‑touch attribution, causal inference, optimization, and experimentation(geo tests, holdouts).
• Strong working knowledge of Generative AI and Agentic AI, including multi‑agent systems, orchestration frameworks, tool use, prompt engineering, evaluation, and AI governance.
• Proficiency in Python, SQL, and modern Data Science and ML libraries; experience with R is a plus.
• Experience with cloud‑based analytics platforms (Azure, AWS, GCP) and scalable data architectures.
• Familiarity with MLOps and LLMOps practices, including model and agent deployment, monitoring, versioning, and automation.
• Strong data visualization and storytelling skills using tools such as Tableau, Power BI, or similar platforms.
• Excellent stakeholder management, communication, and project management skills.
• Ability to work effectively in global, matrixed environments across time zones.

Basic Qualifications

• 9+ years of experience in advanced analytics, with a focus on marketing mix modeling, marketing ROI / effectiveness, or multi‑channel marketing analytics.
• 2+ years in a leadership role managing analytics teams and cross-functional projects.
• STEM degree (Statistics, Computer Science, Engineering, Mathematics, Economics) with quantitative emphasis.
• Expert proficiency in Python, SQL, and marketing analytics platforms; hands‑on experience building or deploying AI / agentic solutions.
• Demonstrated experience in statistical analysis, machine learning, and optimization applied to marketing spend and ROI.

Work Location Assignment: Hybrid

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

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