Director, Data Science - Measurement

ROLE SUMMARY

Global Commercial Analytics (GCA) harnesses the power of data to drive robust analytical insights that inform some of Pfizers most critical business questions. With colleagues across the globe GCAs rigorous analytical expertise is depended on as the compass and decision support for the enterprise. Our dynamic exciting team of subject-matter experts comes from diverse backgrounds and experiences including data science engineering market research and consulting. As a team we collaborate to turn data into meaningful insights that will have a direct impact on patients 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 Pfizers 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 Pfizers 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

• Bachelors 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