Director, Data Science – Measurement

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Role Summary

Global Commercial Analytics (GCA) harnesses the power of data to drive robust analytical insights that inform some of our client’s most critical business questions. With colleagues across the globe, GCA’s rigorous analytical expertise is depended on as the compass and decision support for the enterprise. Their dynamic, exciting team of subject-matter experts comes from diverse backgrounds and experiences, including data science, engineering, market research, and consulting. As a team, they collaborate to turn data into meaningful insights that will have a direct impact on patient’s lives and the future of Pfizer as a data-driven organization.

As a Director, Data Science – Measurement, you will oversee the Measurement team for GCA Data Science and have two direct reports. You will leverage your expertise in data science, statistics, and causal inference to develop measurement frameworks and analytic products to deepen Pfizer’s quantitative understanding of its sales and marketing promotional efforts. You will work in a dynamic, fast-paced environment and will collaborate closely with Pfizer colleagues within the commercial organization.

Role Responsibilities

• Lead the Measurement team for GCA Data Science, managing two individual contributors
• Drive the development of comprehensive analysis and measurement frameworks to understand the impact and ROI of Pfizer’s promotional efforts using advanced statistics and causal inference methodologies
• Provide thought leadership and guidance on promotional and campaign measurement frameworks and methodologies to the broader Data Science team
• Oversee the creation of data infrastructure, tools and products to scale measurement efforts and display results
• Present and clearly articulate methodologies, results and insights to Pfizer commercial leaders in an easy-to-understand manner
• Collaborate closely with colleagues in GCA and Digital to carry out responsibilities of the role

Basic Qualifications

• Bachelor’s degree with a quantitative emphasis such as Data Science, Statistics, Computer Science, Operations Research, Economics, Engineering
• 8+ years of relevant work experience with a focus on marketing science and campaign evaluation. Post-graduate education can substitute for a portion of the work experience requirement
• Expert knowledge and practical application of statistical methods, causal inference techniques and experimental design including A/B testing, Bayesian experimental design, quasi-experiments, statistical matching techniques, observational causal inference and structural equation models
• Fluent in English, both written and verbal
• Expert proficiency in R, Python, Excel and analytics platforms
• Strong understanding of marketing analytics concepts and methodologies
• Experience working with and analyzing large datasets and with data visualization tools and techniques
• Strong problem-solving skills with the ability to think critically and creatively
• Excellent communication, presentation, and storytelling skills, with the ability to translate complex analysis into clear and concise insights for diverse audiences
• Collaborative and results-oriented with a strong work ethic and the ability to manage multiple priorities effectively

Preferred Qualifications

• Advanced degree in a quantitative field
• Commercial pharmaceutical industry experience
• Prior people manager experience
• Consulting experience, along with strong project and client management skills
• Experience with Dataiku DSS

Work Location Assignment: Hybrid