In Early Science, we have highly skilled scientists generating ideas and performing experiments supporting complex drug discovery projects. Our environment is driven by scientific and technical innovation with a high degree of diversity in workflows, data, vendor solutions and in-house builds. As the Product Lead within Augmented Design Make Test Analyse (A-DMTA), you will be responsible for translating R&D scientific needs into valuable technology solutions, line-managing multi-disciplinary teams, and driving the adoption of novel AI and agentic approaches to drug discovery. Working alongside R&D scientists, software engineers, informaticians, ML engineers, analysts and architects, this role places you at the intersection of chemistry, data science, and engineering, with the aim of transforming how AstraZeneca discovers new medicines.
What You'll Do
* Working with globally distributed R&D teams, understand and translate R&D needs and objectives into a clearly defined roadmap and backlog.
* Shape demand with R&D business partners and R&D product owners, matching platform capabilities with R&D need to optimise delivery times and value.
* Convert demand and backlog into clearly defined multi-quarter roadmaps that are backed by R&D and IT stakeholders.
* Ensure successful delivery of initiatives through close collaboration with platform engineering directors and team leads.
* Manage, mentor, and coach a high performing team building cutting edge cheminformatics, modelling and scientific software solutions.
* Own the drug discovery product and data product implementation roadmap.
* Raise awareness, knowledge and effectiveness, and advocate our platform's solutions - facilitate adoption and value realised from their development.
* Develop a sound understanding of and oversee the development of enterprise AI-ready drug discovery data products derived from transactional systems and sources.
* As a platform leadership team member, ensure that the platform joins up into a connected interoperable capability offering a consistent and unified experience for scientific users.
* Stay at the forefront of drug discovery and cheminformatics trends and innovations, bringing external insights from conferences and other sources into the capability.
* Propose technical solutions for complex drug discovery workflows, leading proof of concept efforts with successful high-value selected for production scale.
Qualifications
* PhD or several years' experience working in a drug discovery informatics environment.
* Demonstrable understanding of drug discovery processes and software applications.
* Excellent leadership skills in a matrixed environment.
* Line management experience of technical and scientific teams.
* Expertise in Cheminformatics, ML, or a related field and experience working with one of the cheminformatics toolkits.
* Expertise in one or more languages like Python, Java, Node.js.
* Proficiency in data structures and design patterns.
* Experience working with relational and/or NoSQL databases and knowledge query optimization techniques.
* Excellent team working, verbal, and written communication skills.
* Excellent system-level design and platform thinking.
* Knowledge of agile and scrum delivery methodologies.
Desirable Requirements
* Experience in chemistry data transformation and harmonization to create chemistry data products and services.
* Familiar with coding best practices including testing, code review, and version control.
* Experience with cloud services and tools.
* Experience ETL tools either generic or cheminformatics-specific ones.
* Basic understanding of Machine Learning concepts and MLOps.
* Experience with Docker and Kubernetes.
* Experience with GitOps.
* CI/CD experience with some automation tooling like Jenkins, TravisCI, Github actions, etc.
#J-18808-Ljbffr