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.
AZ2025 Biologic Insights KG
You will join a team committed to building and analysing disease knowledge graphs for oncology, respiratory and metabolic disorders. You will design and apply innovative techniques to wrangle, integrate and analyse scientific data to infer and quantify assertions between drugs, targets and disease processes. You will help design and develop innovative analytical techniques and interrogate knowledge graphs, retrieving biological insight impactful to drug discovery and development. You will also contribute to development of computational models directing research and clinical practices.
Projects and algorithm development will be directed towards enhancing and integrating literature derived knowledge, public data sources, and proprietary clinical and pre-clinical multi-layered data (including genomics, imaging, CRISPR, EHR) to:
- Discover novel drug targets.
- Identify patterns defining distinct patient groups and biomarkers.
- Understand drug mechanism of action and safety.
- Build predictive models directing drug programs.
We are looking for knowledge engineers to help up create intelligent applications powered by knowledge graphs and machine learning. In this deeply technical and close-knit team of data scientists, machine learning engineers and knowledge engineers you will create tools that will advance the standard of healthcare improving the lives of millions of patients across the globe. You will create vocabularies and ontologies to capture vast quantities of biological, medical, chemical, and pharmacological knowledge. You will devise data processing and integration pipelines to expand our knowledge graph with data coming from highly heterogeneous distributed data sources. And you will work with our machine learning engineers and data scientists to populate and exploit the knowledge graph to derive new insights in support for our drug development research.
Our team empowers our scientists from early development to the late stages in drug development, driving innovation and acting as a catalyst for the adoption of the latest advances in Artificial Intelligence and Data Science. We jointly devise novel approaches to drug development and liaise with our platforms team to transition the latest and greatest technologies and algorithms to production. In this role, besides making a meaningful impact to people's lives you will have the opportunity to engage with exciting drug development research, and use your data science, machine learning and artificial intelligence skills to solve challenging technical and scientific problems.
The ideal candidate will possess a blend of computational science skills, successful experience building quality applications related to NLP and machine learning in a scientific environment. You will be part of our exciting new knowledge graph project – both building an internal KG across science but also working in partnership with some of the latest start-ups.
- Latest NLP tooling, pipeline and templated analytics
- Research and apply new algorithms and methods to relevant business problems
- Understanding & application of fine-tuning language models
- Devise rich vocabularies and ontologies to best support the knowledge graph and the integration of disparate data sources
- Design, develop, test and maintain knowledge graph creation, consistency checking, maintenance analysis and debugging tools.
- Integrate new structured and unstructured data sources into a coherent and consistent knowledge graph
- Work closely with data scientists, machine learning, engineering and platform teams
- Help other teams to access and leverage the knowledge graph to answer research questions
- Develop a robust understanding of relevant AZ internal and external content sources and their provenance, quality and structure, to support optimal use
Candidate Knowledge, Skills and Experience
- Masters / PhD in Machine Learning, Computer Science, Mathematics or similar field with 2+ years of experience specialising in natural language processing or deep learning.
- Strong coding and software engineering skills such as Python, Java.
- Experience in using unsupervised and supervised methods over unstructured data: especially with search, text analytics and NLP.
- Deep technical skills in knowledge representation, reasoning, graphs, natural language processing, data integration or artificial intelligence
- Experience with graph technologies would be useful
- Experience building large scale data processing pipelines
- Working knowledge of cloud environment (AWS preferred), Hadoop/Spark, SQL
- Knowledge of scraping documents and document extraction beneficial.
- Ability to explain complex methods and techniques to a non-technical audience
Department – Data & Analytics, S&EUIT
Science and Enabling Units IT is a global IT capability supporting Drug Research, Drug Development, Product & Portfolio Strategy, Medical Affairs, Finance, HR, Compliance, Legal and Global Business Services. We are organized around 7 key capability areas: Business Partnering, Solution Delivery, Architecture, Application Support, Data & Analytics, Change & Operations, operating out of sites across the US, UK, Sweden, India and Mexico.
Data & Analytics provides analytics and data insight services and solutions critical to the Data & AI/ML emerging strategy and mission of S&EUIT and AZ. D&A is organized into teams specializing in Information Architecture, Data Engineering, Data Visualisation, Knowledge Management, Data Science, Data Analysis and Information Governance.
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.