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Director, Data Science and Ai

4 months ago

New York, United States Pfizer Full time

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.

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 field.
- Advanced degree with 5+ years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
- Extensive experience using data science models to solve problems in a business environment setting.
- Experience with influencing commercial strategies and tactics, experience in pharmaceutical or healthcare industry is preferred.

Relevant Experience
- Extensive expertise and experience with, both traditional SQL and modern NoSQL data stores including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks.
- Strong experience with machine learning technology, such as: big data stack, Python, R, and visualization techniques.
- Deep understanding of artificial intelligence concepts, experience with AI frameworks and libraries such as TensorFlow or PyTorch is also valuable.
- Exceptional ability to connect, integrate and synthesize analysis and data into a meaningful ‘so what’ to drive concrete strategic recommendations for brand tactics.
- Skilled of describing relevant caveats in data or in a model and how they relate to business question or recommendation.
- Ability to be flexible, prioritize multiple demands and deal with ambiguity.

Competencies
- Cross-functional influence: Expert in creating strategic direction and velocity through winning and influencing business partners to make complex decisions that influence multiple business areas.
- Growth Mindset: Eva