VP, Data Science - Global Commercial Analytics

About the Role

Key Responsibilities

• Deliver data science driven insights and solutions for all of commercial functions, partnering with senior functional leads to develop and implement models, insights, and data products that align with strategic priorities.
• Lead and mentor a team of data scientists and managers, organizing analytical processes and workflows, and fostering high performance within a dynamic environment.
• Apply advanced machine learning techniques to develop analyses and tools that directly impact revenue and resource optimization.
• Build and lead enterprise teams to develop end-to-end ML/AI solutions at large scale in the Cloud.
• Conceptualize, document, and deploy complex analytical plans to address business problems.
• Communicate insights effectively through storytelling, data visualization, and executive-level presentations.
• Partner with senior leaders to understand business goals, advise on data strategies, and produce repeatable, impactful outcomes.
• Collaborate with the digital engineering team to develop AI/ML roadmaps and enterprise AI strategies.
• Manage econometric analytics projects through all phases, including data quality, modeling, statistical analysis, visualization, and presentation.
• Lead ongoing and ad-hoc analyses and predictive analytics to provide actionable insights at tactical and strategic levels.

Requirements

• 15+ years of relevant experience in data science/machine learning and 10+ years of managerial experience.
• Bachelor's Degree required; advanced degree in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field; Ph.D. highly preferred.
• Expertise in applied regression techniques including Linear, Logistic, Mixed models, Time Series, General Linear Models, and Simultaneous Equations.
• Experience with neural networks, deep neural nets, boosted trees, support vector machines, GAN models, and neural network models for sales forecasting.
• Proficiency in statistical data analysis and machine learning algorithms for unsupervised and supervised learning.
• Experience with algorithm development in graph mining and social network analysis is a plus.
• Ability to design end-to-end scripted analytics solutions using SAS, SQL/TeraData, Spark, Hadoop, Databricks, Snowflake, and Python.
• Strong knowledge of data pipelines, data storage systems (relational and NoSQL), ETL processes, SDLC in data engineering, and performance optimization.
• Background in healthcare, Pharma, or health payments analytics preferred.
• Excellent communication, storytelling, and data visualization skills for engaging senior executives.

Nice to Have

• Experience in B2B and/or B2C marketing.
• Algorithm development in graph mining and social network analysis.

Qualifications

• 15+ years of experience in data science/machine learning.
• 10+ years of managerial experience.
• Bachelor's Degree; Ph.D. preferred.

Benefits & Perks

• Competitive annual base salary ranging from $280,400 to $467,400.
• Eligibility for Pfizer's Global Performance Plan with a bonus target of 30% of base salary.
• Participation in share-based long-term incentive programs.
• Comprehensive benefits including 401(k) with matching contributions, additional retirement contributions, paid vacation, holidays, personal days, caregiver/parental and medical leave, health benefits (medical, dental, vision, prescription).
• Relocation assistance may be available.
• Onsite requirement of 2.5 days per week.