Director, Data Science and AI

The Data Science & AI team with Commercial Analytics & AI (CAAI) organization is committed to transforming data into actionable intelligence, empowering Pfizer to stay competitive and innovative in today's data-driven landscape.  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 Director, Data Science and AI who will be responsible creating and delivering data-driven insights and/or AI-powered analytics tools to Pfizer’s Commercial organization and will either support a brand or therapeutic area or be part of a team designing, delivering, and upgrading innovative capabilities. This includes influencing business partners and leading the execution and interpretation of AI/ML models, framing problems, and shaping solutions with clear and compelling communication of data-driven insights.

This role is dynamic, fast-paced, highly collaborative, and covers a broad range of strategic topics that are critical to our business. The successful candidate will join CAAI colleagues worldwide that are driving business transformation through proactive thought-leadership, innovative analytical capabilities, and their ability to communicate highly complex and dynamic information in new and creative ways.

**This is an individual contributor role.

Product / Brand and Therapeutic Area (TA) Insights 

• Lead advanced analytical models, predictive algorithms, and AI-powered tools to extract actionable insights to drive US Commercial strategies and tactics.
• Influence end-to-end delivery of data science insights, from framing the business question, designing the solution, and delivering recommendations. 
• Break down technical concepts into digestible insights and guide diverse stakeholders how to interpret.
• Continuously evaluate and enhance existing brand /TA data science capabilities, identifying opportunities for optimization and innovation to drive greater business impact and ROI.
• Build strong relationships with key stakeholders, effectively communicating the value proposition of data science and fostering a culture of data-driven decision-making.

Collaborate Cross-Functionally as a Brand/TA Focused Analytics POD

• Collaborate within the analytics POD, coordinating efforts with the Insight Strategy & Execution and Market Research Insights counterparts to develop and execute a comprehensive brand analytics plan.
• Deliver consolidated insights and actionable recommendations to US Commercial teams, ensuring alignment with strategic objectives and insights findings.
• Represent data science function and capabilities in Analytic POD meetings.
• Work closely with cross-functional teams to ensure seamless integration of brand analytics insights into decision-making processes and strategic initiatives.

Innovative Data Science Capabilities

• Lead the design, delivery, and scaling of innovative solutions across the organization – from pilot phases to full-scale implementation.

• Drive the delivery process, leveraging agile methodologies and best practices to efficiently progress from pilot projects to scalable solutions, while maintaining a focus on quality and innovation.
• Steer the upgrading and refining of capabilities based on feedback and insights gathered during pilot phases, continuously enhancing the effectiveness and relevance of implemented solutions.
• Play a key role in the organizational transformation by championing innovation, fostering a culture of experimentation, and facilitating the adoption of new capabilities at scale.

Cross-Functional Collaboration

• Work closely the Analytics Engineering to ensure the data ecosystem is conducive for data science modeling purposes.
• Partner with Digital teams to enhance data science capabilities, aligning efforts to leverage digital data sources effectively.
• Foster collaboration with teams to ensure seamless integration of data science initiatives across the organization's infrastructure, promoting efficiency and effectiveness in leveraging data for informed decision-making.

Qualifications

• Minimum of bachelor’s degree with 10+ years of experience, preferably in engineering, economics, statistics, computer science, or related quantitative f