Associate Director, AI & NLP Specialist, Oncology

at  AstraZeneca

At AstraZeneca, with our portfolio, our pipeline, and our people, we strive to revolutionize cancer care with our bold ambition to provide cures for cancer in every form. Our broad pipeline of next-generation medicines is focused principally in lung, breast, gastrointestinal, GU and haematological cancers. We follow the science to deliver life-changing treatments and increase the potential to save the lives of people around the world.
If you are passionate about science and data-driven decision making, explore the possibility of joining us as an Associate Director, AI & NLP specialist to craft our oncology portfolio trials via efficient use of clinical information.
The position sits within Oncology Information Practice department, a part of the Oncology Biometrics organisation. As part of a diverse global team, you will contribute to the drug development process by empowering the business to perform at it’s peak and lead a new way of working, combining ground-breaking science with leading digital technology, platforms and data. We do this with a passion – to impact lives through data, analytics, AI, machine learning and more.

ESSENTIAL REQUIREMENTS

Bachelors or Master’s degree with proven experience in industry, Mathematics, Computer Science, Computational Linguistics, Engineering, Physics, Statistics, Computational Sciences, or a related quantitative subject area.
Experience in 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.
Demonstrated expertise in advanced statistical modelling, or broader aspects of applied mathematics such as dynamical systems or optimisation.
Understanding of algorithm design, development, optimization, scaling and applications.
Strong proficiency in Python coding skills.
Experience in solving NLP problems, such as Search, NER, language generation, classification using the latest SOTA deep learning models and frameworks (Hugging Face, BERT, PyTorch, spaCy)
Solid understanding of cloud environment (AWS preferred)
Ability to articulate complex methods and techniques in a clear and understandable manner to non-technical collaborators.
Consistent track record of strong leadership and successful project management in NLP and AI initiatives.
Excellent communication and presentation skills, with the ability to convey complex AI concepts to non-technical partners.
Knowledge of AI ethics and responsible AI practices, with a commitment to ethical and fair AI principles in all projects and initiatives.

ABOUT THE ROLE:

As a member of our team, you will solve sophisticated challenges in natural language processing, demonstrating advanced expertise to drive data science solutions. You will apply both foundational and innovative techniques to manipulate and process structured and unstructured data, using business domain knowledge to develop and deploy innovative algorithms to derive valuable business and scientific insights. Your role will involve contributing to the development of intelligent applications that harness knowledge graphs, embeddings, and machine learning. Collaborating with data scientists, machine learning experts, and information scientists, you will build and utilise tools that elevate healthcare standards, ultimately improving the lives of millions of patients worldwide. Your efforts will contribute to the advancement of our ontologies and natural language understanding tools, enabling the capture of extensive volumes of biological, medical, and clinical knowledge.
We are seeking a candidate who possesses a balanced blend of theoretical and practical skills in applying NLP, AI and machine learning in a scientific environment.

WHAT YOU WILL DO:

Design, implement, and support modelling solutions aimed at extracting insights from datasets for scientific and business applications. This includes integrating data from multiple different sources and modalities and includes the application of specialized approaches in classification, regression, clustering, NLP, graph theory and/or other techniques.
Leverage advanced data science expertise to cross-functional projects and shape delivery of data science solutions that drive value to Oncology Biometrics & AstraZeneca
Apply a diverse range of data science methodologies, developing novel data science solutions where the off-the-shelf methodologies do not fit.
Translate unstructured, business challenges into appropriate data problems, models and analytical solutions.
Ceate data and analysis pipelines to deliver clinical insights and reusable capabilities.
Explore and implement novel methods in optimization, machine learning, generative AI, data analysis, and data visualization.
Effectively communicate results to both technical and non-technical collaborators at different levels within the organization.
Research and develop predictive models and computational methods to guide decision-making within project parameters and established approaches.
Collaborate in multidisciplinary cross-functional teams with world leading product managers, designers, engineers, clinicians, data scientists, biological experts, statisticians and IT professionals.
Disseminate findings for conferences and in peer reviewed journals.
Build effective relationships with established range of partners 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.
Provide data science support to cross-functional projects, contributing to the delivery of defined solutions that drive value for AstraZeneca.
Operate in compliance with regulatory and evidential requirements.
Continuously develop, maintain, and apply ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science.
Implement working practices to ensure that data science work is delivered to robust quality standards and aligned to defined governance frameworks and policies.
Work autonomously with limited direct supervision from senior team members. You will also provide support to other AI Scientists promoting standard processes across multiple domains, and/or collaborator groups.
Independently keep own knowledge up to date and learn from senior team members, proposing appropriate training courses for personal development.