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The Commercial Scaled Analytics team, a division within Analytics, Data Learning, delivers both central expertise counsel and self-service capabilities across Pfizer Commercial businesses, building and executing plans, priorities, infrastructure, and competencies that support analytic- driven insights for the business.The Brand and Customer Analytics (BCA) Center of Excellence is a global.

Responsibilities

  • In partnership with regional teams proactively identify opportunities to improve go-to-market strategy by gaining additional insight into customer interactions and their impact on brand performance.
  • Serve as the methodology/analytics expert in identifying the right approach to address brand and customer analytics needs within a region/business unit.
  • Leverage experience, the catalog of existing BCA analytic offerings, and the larger Pfizer analytics network to identify the right methodologies to address business needs.
  • Propose a project plan resting on a solid foundation of a scalable and innovative analytical solution, provide the right resourcing for long term success, and timelines that address business needs.
  • Collaborate with the rest of the Pfizer Digital organization on the project scope.
  • Lead the analytics project scoping, modeling/analytics, implementation, and provide a roadmap for the capability – within the brand/business unit, and across.
  • Manage multiple analytics and commercial stakeholders.
  • Manage budgets associated with assigned activities.
  • Direct workload of flexible resources and identify the need for changes in flexible resources.
  • Be accountable for continuous improvement and identification/utilization of new capabilities to maximize the competitive advantages of the business
  • Serve as the advocate for customer analytics techniques that bring Pfizer closer to customer centric operating model – one analytics project at a time.

Qualifications

  • 5 yrs + of experience in pharmaceuticals and/or pharma consulting strongly preferred.
  • Advanced quantitative techniques and their applications to customer analytics space: clustering/segmentation, classification/customer propensity, etc.
  • Hands-on experience with Statistical and Machine Learning concepts.
  • Knowledge of supervised and unsupervised ML techniques and their applications to business / customer analytics problems.
  • Demonstrated strong strategic, conceptual and analytical thinking.
  • Curiosity with the latest advancements in the data science techniques
    (e.g. deep learning, NLP) and a point of view of their application to
    customer analytics.
  • Knowledge and point of view on data stacks, martech stacks, and customer experience ecosystems.
  • Dataiku, Tableau, Python (or R), SQL
  • Agile and Jira-enabled PM experience preferred.
  • Strong communication skills.


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