48 applicants

Company

Original Job Post

Pfizer · 2 days ago

Sr. Director/TL, Data Science & AI

Pennsylvania, United States

Full-time

Hybrid

Director

$205K/yr - $342K/yr

15+ years exp

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Responsibilities

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

Build and lead a team of data scientists, organizing analytical processes and workflows, and mentoring/developing the managers what work on your team as well as junior team members.

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 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.

Collaborate within the analytics POD, coordinating efforts with the Insight Strategy & Execution and Market Research Insights counterparts to develop and execute AI capabilities 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.

Qualification

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Applied EconometricsStatisticsData MiningMachine LearningMathematicsOperations ResearchIndustrial EngineeringSQLNoSQLHadoopSnowflakeDatabricksPythonRData VisualizationArtificial IntelligenceAI FrameworksTensorFlowPyTorchCommercial StrategyPharmaceutical Industry KnowledgeHealthcare Industry KnowledgeSecondary Data ManagementStrategic ThinkingData AnalysisBusiness AcumenProblem-SolvingTeam ManagementCommunicationAdaptability

Required

Bachelors degree with 15+ years of experience, preferably in engineering, economics, statistics, computer science, or related quantitative field.

Advanced degree preferred, 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 building, managing, and growing high performing & diverse teams across geographies.

Extensive 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.

Experience with influencing commercial strategies and tactics, experience in pharmaceutical or healthcare industry is preferred.

Extensive experience in management of secondary data with application to real-world data.

Proven 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.