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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.
- 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.
- 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
- 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.