AstraZeneca is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development, and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. At AstraZeneca, we're proud to have a unique workplace culture that inspires innovation and collaboration. Here, employees are empowered to express diverse perspectives and are made to feel valued, energized, and rewarded for their ideas and creativity.About the RoleWorking as part of a global team of AI Engineers and technical specialists, you will have the opportunity to develop and deploy AI algorithms throughout the delivery lifecycle, from ideation, PoC, MVP to cloud production. This will involve rapidly prototyping ideas in response to complex problem statements, formulating and working on scalable ML pipelines, and partnering with other AI scaling engineers to build reusable AI assets and services that are shared throughout the Enterprise.Key AccountabilitiesProvide expertise in a broad range of AI/ML disciplines and be able to use software to respond to and solve complex business and research problems.Translate and formulate unstructured business problems into the appropriate data problem, model, and analytical solutions.Contribute towards and help maintain cloud ML pipelines across a portfolio of projects.Research and develop advanced AI models and computational methods to guide decision-making within project parameters and established approaches.Perform AI research, including establishment of hypotheses that can be approached using computational methods and tools.Present or publish findings for conferences and in peer-reviewed journals where appropriate.Build effective relationships with a range of stakeholders to ensure utilization and value of information resources and services. Clearly and objectively communicate results, as well as their associated uncertainties and limitations within agreed frameworks.Minimum RequirementsBSc/MSc/PhD degree in Mathematics, Statistics, Computer Science, AI, or related quantitative field.Advanced software development skills in at least two standard data science languages (Python is essential) and familiarity with database systems (e.g., SQL, NoSQL, graph).Hands-on experience in the Python ecosystem for data science, machine learning, and AI (Scikit-learn, Pytorch, Tensorflow, Numpy, Pandas).Thorough understanding of classical mathematical and statistical concepts such as regression, inference, sampling, Bayesian methods, and optimization.Working knowledge of cloud environments and experience writing AI software as part of agile delivery teams.Proven expertise in software development best practices and principles (software architecting, linting, CI/DI, unit tests, OOP, Git).Excellent written and verbal communication, business analysis, and consultancy skills.Strong bias for action and results.
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