Manager, Data Science and AI delivering actionable insights and AI-powered analytics tools for Pfizer’s Commercial organization. Leading execution of AI/ML models and facilitating communication of data-driven insights.
Responsibilities
Deliver advanced analytical models, predictive algorithms, and AI-powered tools to extract actionable insights to drive Commercial strategies and tactics.
Support the 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.
Build strong relationships with key stakeholders, effectively communicating the value proposition of data science.
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 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.
Work closely with 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 other 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.
Requirements
Minimum of bachelor’s degree with 3+ years of experience, preferably in engineering, economics, statistics, computer science, or related quantitative field.
Advanced degree preferred with 0~2 years of experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
Experience using data science models to solve problems in an education or business environment setting.
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.
Experience with machine learning technology, such as: big data stack, Java, Python, R, Scala and visualization techniques, including Dash, Tableau and Angular.
Experience in understanding brand content, strategy, and tactics.
Ability to effectively utilize dashboards and data products to derive insights.
Experience with supporting commercial strategies and tactics, experience in pharmaceutical or healthcare industry is preferred.
Experience in management of secondary data with application of real-world data.
Ability to partner with cross-functional teams (Commercial, Medical, Operations) to execute brand tactics.
Able to connect, integrate and synthesize analysis and data into a meaningful ‘so what’ to drive concrete strategic recommendations for brand tactics.
Capable of describing relevant caveats in data or in a model and how they relate to business question.
Ability to be flexible, prioritize multiple demands and deal with ambiguity.
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