Director, Commercial Data Science & AI

Associate Director, Commercial Data Science & AI 

The US - Director, Commercial Data Sciences & AI is a key leader in the Commercial Data Science & AI team whose mission is to take a patient-centric, data-driven approach to personalize and transform healthcare delivery to the millions of patients along with a multi-disciplinary team of physicians who care for them. This position entails working in close partnership with multi-functional Science, Medical, and Business leaders to identify, prioritize, and develop Data Science, AI, and Advanced Analytics Platforms & Products across AZ Oncology and Bio-pharma businesses. The scope of this role is Global with a focus on US markets where AstraZeneca’s life-changing medicines are approved to help patients live longer and realize AZ’s bold ambition of eliminating Cancer as a cause of death.  

The team is responsible for value creation through innovation at a global scale. In addition to outstanding technical skills, the ability to communicate and influence a diverse stakeholder set is crucial. Not infrequently, the problems we solve are first identified by its senior members – introducing and gaining traction for these concepts requires tact and subtlety.  

Key Responsibilities:  

• Develop a deep understanding of the business and its core markets.  

• Leverage AI/ML, mathematical programming, and statistical modeling to develop solutions that create a competitive advantage for our commercial organization.  

• Be responsible for the full solution architecture cycle: identification & definition of business questions/opportunities, data acquisition & preparation, model implementation & optimization, and method of deployment to the consuming system or team.  

• Collaborate with ML Ops to prepare and document Skunkworks solutions for transition to maturity/industrialization team.  

• Collaborate with matrix teams (sales, marketing, IT, external vendors, etc.) to ensure effective and efficient deployment of capabilities.  

• Actively seek out, develop, and share best practices.  

• Stay abreast of the evolving technical landscape, and remain current on the major data science libraries/stack  

• Incentivize and pursue continuous improvement of existing capabilities and skills.  

• Lead onshore and offshore external consultants.  

Competencies  

Minimum Requirements  

Bachelor’s Degree plus 5-7 years of progressive professional work experience in mathematics, computer science, engineering, physics, statistics, economics, computational sciences, or a quantitative field. 

• 7+ years of qualified professional experience can be substituted for Bachelor’s degree 

• Track record of Developing Data Science and AI products that have generated business value, and impact across multiple Industries.  

• In-depth experience with modern data science approaches, including unsupervised and supervised classification and regression algorithms such as k-means clustering, support vector machines, random forests, neural networks, and deep  

• 8+ years of hands-on experience in the application of data science methods on large and disparate datasets, specifically:  

• Statistical Analysis and Modelling: (e.g. Design of Experiments, Time Series Analysis, Regression Analysis, Bayesian methods, etc),  

• Hands-on experience and theoretical expertise in modern deep learning (e.g. transformers).