ROLE SUMMARY
Pfizer Global Commercial Analytics (GCA) harnesses the power of data to drive robust analytical insights that inform some of Pfizer’s most critical business decisions. Our dynamic team of subject-matter experts comes from diverse backgrounds — including data science, engineering, market research, and consulting — and collaborates to turn data into meaningful insights that have a direct impact on patients’ lives and the future of Pfizer as a data-driven organization.
GCA is expanding its footprint in Mexico through the establishment of a dedicated analytics capability center to meet growing business demand and accelerate the development of innovative analytics solutions for the US Commercial Division.
The Lead, Data Science - GCA Mexico Analytics Center is a hands-on role that will oversee the Data Science team within the GCA Mexico Analytics Center. This leader will drive data-driven decision-making across Pfizer’s US marketing organization, partnering closely with brand and Chief Marketing Officer (CMO) stakeholders to develop cutting-edge analytics capabilities, measurement frameworks, and AI-powered solutions that directly impact marketing performance and business outcomes.
The ideal candidate is an expert in data science with deep experience in marketing analytics, machine learning, and AI — and thrives at the intersection of advanced technology and real-world business impact.
ROLE RESPONSIBILITIES
- Lead and develop a team of data scientists, fostering a high-performing, collaborative environment and providing hands-on coaching and career development within the GCA Mexico Analytics Center.
- Provide strategic leadership in the development and execution of marketing analytics capabilities, including brand measurement, channel optimization, targeting, and AI-driven innovation initiatives.
- Lead the design and deployment of advanced measurement frameworks, including impact measurement experiments (A/B testing, ANCOVA, econometric models) to evaluate and optimize US commercial marketing investments.
- Drive the development and implementation of machine learning and AI solutions that generate actionable insights, automate analytical workflows, and enhance the speed and precision of commercial decision-making.
- Identify unmet analytical needs across brand and marketing teams, and guide the strategic roadmap for developing new capabilities that advance GCA’s innovation agenda.
- Partner cross-functionally with brand, CMO organization, Marketing, Finance, and Technology teams to align analytics capabilities with broader business objectives and embed insights into strategic planning.
- Design, develop, and maintain reusable data science assets, pipelines, and frameworks to improve operational efficiency and scalability across the team.
- Serve as a hands-on technical leader proficient in Python, R, and SQL, with the ability to translate complex analytical outputs into clear, compelling narratives for senior business stakeholders.
QUALIFICATIONS
Basic Qualifications
- Education & Experience: BA/BS with 7+ years of experience in data science or advanced analytics; MS/MBA with 6+ years; or PhD with 2+ years. A minimum of 3 years in a people leadership or project lead capacity is required.
- Technical Expertise: Expertproficiency in Python and SQL. Hands-on experience applying machine learning techniques (supervised, unsupervised, deep learning), AI-driven approaches, and statistical methods to solve real-world commercial analytics problems. Hands-on experience working with modern engineering tooling including GitHub, GitHub Copilot (or similar AI coding assistants), and DevOps practices such as CI/CD, version control workflows, and automated deployment.
- Measurement & Analytics: Demonstrated experience in marketing measurement methodologies, including impact measurement experimentation (A/B testing, ANCOVA, econometrics), marketing attribution modeling, and marketing mix modeling (MMM).
- AI & Innovation: Familiarity with the application of generative AI, large language models (LLMs), and automation techniques to enhance analytics workflows and accelerate insight delivery.
- Business Acumen: Ability to identify unmet analytical needs and translate them into scalable capability roadmaps.
- Communication: Excellent communication, presentation, and storytelling skills with the ability to translate complex data science outputs into clear and actionable insights for diverse audiences including senior leadership.
- Collaboration: Collaborative and results-oriented, with demonstrated ability to manage multiple priorities and influence cross-functional partners across business units and functions.
- Education Background: STEM degree (Science, Technology, Engineering, or Mathematics) with quantitative emphasis — such as Statistics, Computer Science, Operations Research, Economics, Actuarial Science, or Engineering — preferred.
Preferred Qualifications
- Industry or consulting experience in pharmaceutical marketing analytics or commercial data science.
- Subject matter expertise in one or more of the following: machine learning, Bayesian statistics, causal inference, or deep learning applied to commercial use cases.
- Knowledge of pharma-specific datasets such as IQVIA, claims data, or patient-level analytics.
- Experience building or contributing to AI-powered analytics products or platforms.
- Experience working in or with a Global Capability Center (GCC) or shared services analytics environment.
- Project management skills and experience coordinating across global, cross-functional teams.
Work Location Assignment: Hybrid
EEO (Equal Employment Opportunity) & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, or disability.


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.

Marketing and Market Research
