Director, Commercial Data Science & AI

At AstraZeneca, we're not afraid to do things differently. We're resetting expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, groundbreaking and ground-breaking methods and bringing unexpected teams together.

The Oncology therapy area at AstraZeneca is unparalleled. We have built and strategically acquired one of the most promising Oncology pipelines in the industry. You will be among inspiring oncology industry leaders who will keep you engaged and empower you to be the best. We seek out opportunities to do dynamic and significant work which means we won't just follow the same course of action time and again if we can see potential in a different way of building life changing medicines.

Director, Commercial Data Sciences & AI is a key member of the OBU Data Sciences team supporting the delivery of data science capability ad solutions across the OBU commercial business. This responsibility includes working closely with cross functional business leaders to help match the potential of effective data science applications to the most urgent business questions and needs.

This role will build delivery the data science expertise to deliver business solutions which offer innovative and effective approaches based on rich data science experience to enhance commercial execution globally. The role will sit in the Commercial Operations Team and is expected to make a strong contribution to the commercial business at Global and Priority market levels.

Typical Accountabilities
  • Delivery of novel modelling solutions designed to drive the interrogation of datasets for insights in scientific and business application areas. These solutions include the application of specialized approaches in classification, regression, clustering, NLP, image analysis, graph theory and/or other techniques.
  • Using domain-specific understanding, translates unstructured, complex business problems into the appropriate data problem, model and analytical solutions across multiple projects
  • Oversee the researching and developing of predictive models and computational methods to guide and influence decision-making outcomes
  • Develop effective relationships with commercial and medical leaders to ensure utilization and value of information resources and services in multiple projects.
  • Responsible for advanced data science expertise to multiple cross-functional projects and drive delivery of complex data science solutions that drive value to AstraZeneca
  • Lead and apply ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science to influence functional practices.
  • Collaborates across the AstraZeneca Data and AI community to develop best practices and cross functional opportunities that drive value
  • Oversight of partnerships with multiple third parties, academic or outsourced partners to shape and drive project outcomes and knowledge building

  • Bachelors Degree (or equivalent numbers of years of experience) in mathematics, computer science, engineering, physics, statistics, economics, computational sciences or a related quantitative discipline.
  • 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 learning. May also have expertise in advanced statistical modelling, or broader aspects of applied mathematics such as dynamical systems or optimization.
  • Significant experience in the modelling of complex datasets in applied business and/or scientific application domains
  • Advanced software development skills in at least two of the standard data science languages (such as R, Julia or Python) and familiarity with database systems (e.g. SQL, NoSQL, graph)
  • In-depth experience of manipulating and analyzing large high dimensionality unstructured datasets, drawing conclusions, defining recommended actions, and reporting results across stakeholders
  • Understanding of algorithm design, development, optimization, scaling and applications
  • Excellent written and verbal communication, business analysis, and consultancy skills

  • Master or PhD degree in mathematics, computer science, engineering, physics, statistics, economics, or a related quantitative discipline.
  • Comfortable working in high performance computing or cloud environment
  • Proven track record of publishing relevant predictive modelling results and tools in peer-reviewed journals, conferences, and other scientific proceedings.
  • Experience in life sciences and healthcare
  • Experience in novel methods development and application
  • Experience in a complex global organization
  • Experience in leading and managing junior colleagues
  • Experience in influencing and controlling budgets

Why AstraZeneca?

At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognizing their potential. Join us on our journey of building a new kind of organization to reset expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together. Interested? Come and join our journey.

Are you already imagining yourself joining our team? Good, because we can't wait to hear from you.

Where can I find out more?

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AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

10001255 G DAAS Oncology