.Company 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.Department - AI Strategy & InnovationThe AI Strategy & Innovation Team is a global team of highly experienced, skilled AI engineers and professionals, passionate about delivering state-of-the-art services and products within R&D IT. AI has the potential to transform every step of the R&D pipeline. Through recent advancements in technology, we are now collecting trillions of points of data and have the opportunity to harness that data for analytics and insight that will lead to a new generation of medicines capable of addressing the world's most challenging unmet medical needs. The mission of our team is to transform the way R&D uses data, analytics, and AI to discover and develop medicines. In order to achieve this, we partner with scientific teams to deliver cutting-edge capabilities, products, and platforms that enable scientists to accelerate medicines that are safe and effective for patients.RoleIn this role, you'll own the technical delivery and implementation of our internal deep learning capabilities. In addition, this role will be the site leader for AI Strategy & Innovation in Barcelona. You will build a community of data experts, driving team cohesion, engagement, morale, and sharing of best practices - making it both high performing and a great place to work.Key AccountabilitiesWork closely with the Product Lead for Deep Learning to build a roadmap and vision for our capability build that meets key strategic R&D needs.Drive clear communications, accountability across the team and effective ways of working.Prioritize (from a technical perspective) backlog features with the Product Lead, Project Manager, and key stakeholders.Drive technical direction and architectural decisions for Deep Learning, ensuring we have the right technology to enable data scientists and AI engineers to work efficiently and accurately.Drive the Deep Learning engineering roadmap, in line with the scientific vision.Remain up to date with machine learning literature and modeling approaches.Actively participate in both internal and external opportunities to publish and present progress of the Deep Learning team.Work closely with project managers and Product Lead to optimize platform budgets and work alongside aligned projects to ensure provision of balanced and appropriate skillsets in delivery teams
