Ai Lead

hace 2 meses

Barcelona, España AstraZeneca A tiempo completo

**ABOUT ASTRAZENECA**

AstraZeneca is a global, innovation-driven BioPharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious disease. But we’re more than one of the world’s leading pharmaceutical companies.

At AstraZeneca we’re dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development.

**ABOUT THE **OPERATIONS IT **TEAM**

Operations IT is a global IT capability supporting the Global Operations organisation. We business partner with Operations capability areas: Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics and Global External Sourcing and Procurement. We operate out of Operations hub sites including in the UK, Sweden, US, and China; and out of our Global Technology Centres in India and Mexico.

Here our work has a direct impact on patients - transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine learning and more.

It’s a dynamic and challenging environment to work in - but that’s why we like it. There are countless opportunities to learn and grow, whether that’s exploring new technologies in hackathons, or transforming the roles and work of colleagues, forever. This is your chance to be part of a team that has the backing to innovate, disrupt an industry and change lives.

**THIS IS WHAT YOU’LL DO**

We are recruiting a Associate Director AI Lead to join our newly established Data, Analytics & AI group for Operations IT spanning various business areas such as Develop, Manufacture, Supply Chain, Quality and Procurement.

You will also be responsible to manage or coordinate the work of a team of AI data scientists. The role will also be responsible for influencing a range of internal stakeholders and manage external collaborations and vendors to deliver effective solutions in the Operations space.

Typical accountabilities include:

- 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.
- Define and oversee training and advice to collaborators on optimal use of key data, analysis platforms and the appropriate use of complex data science or modelling solutions.
- Develop effective relationships with senior stakeholders to ensure utilization and value of information resources and services in multiple projects.
- Responsible for advanced data science and operations research expertise to multiple cross-functional projects and drive delivery of complex data science solutions that drive value to AstraZeneca Operations.
- Leads (3-10 person) data science projects of defined scope, potentially across multiple locations.
- Responsible for ensuring project deliverables are clearly defined and delivered within the relevant portfolio and manage stakeholder expectation for associated risks and limitation of outputs results.
- 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.

**YOU WILL NEED TO HAVE**
- Bachelors Degree (or equivalent numbers of years of experience) in operations research 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 optimisation.
- Strong knowledge of software development principles.
- Proven experience in coding 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 analysing large high dimensionality unstructured datasets, drawing conclusions, defining recommended actions, and reporting results across stakeh

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