AI & Computational Tools Leader for Oncology Discovery

AstraZeneca GmbH; Cambridge; On-site; GBP 78,000 - 110,000; Full time

Job summary

AstraZeneca Cambridge is seeking an Associate Principal Scientist to lead AI-powered tools development for Oncology R&D. You will combine immunology and computational biology with data engineering to design scalable AI workflows and data platforms, partnering with wet-lab scientists and IT.

In this fixed-term role, you will provide technical leadership, build reusable software, mentor colleagues, and drive adoption of AI-enabled approaches across the discovery group, shaping the future of

Qualifications

• Demonstrated experience leading complex computational or AI initiatives from concept through implementation, deployment and adoption within a scientific environment.
• Demonstrable experience using agentic AI frameworks, LLM integration or AI-assisted coding tools such as GitHub Copilot, Claude Code or similar in a research or production context.
• Demonstrable experience developing and deploying tools for use by others, such as Shiny applications, automated reporting systems or shared analysis packages, with confidence in version control and collaborative software-development practices.
• Demonstrable experience building research data infrastructure that enables structured, quality-controlled and reproducible data, for example through LIMS schemas, electronic laboratory notebook workflows, structured databases or reproducible data pipelines with automated validation and quality control.
• Strong proficiency in Python and/or R, and experience of large-scale data management.
• Demonstrated ability to support adoption of new computational capabilities across research teams, including user engagement, documentation, training and communication with scientific leadership.
• Evidence of influencing scientific or technical direction beyond an immediate project team through technical leadership, best-practice development, mentoring or capability building.
• Strong interpersonal and collaboration skills, with a track record of working effectively across wet-lab and dry-lab teams in a matrixed environment.
• Experience preparing written scientific reports and delivering oral presentations.

Responsibilities

• Lead the design, development, deployment and lifecycle management of AI-powered tools and workflows, including data-wrangling pipelines, visualisation applications, agentic AI solutions and LLM-integrated tools. Ensures solutions are maintainable, adopted by users and deliver measurable scientific value.
• Lead the development and evolution of data infrastructure and data standards for the discovery group, with the intended outcome of structured, quality-controlled and reproducible data that are ready for analysis and AI applications.
• Act as an AI Architect and technical subject matter expert for the department, defining best practices, guiding technology choices, influencing AI strategy and driving adoption of reusable code, packages and tools across teams.
• Identify, prioritise and lead delivery of AI and computational capability projects that address strategic scientific challenges, balancing innovation, technical feasibility, governance, sustainability and user adoption.
• Mentor and support colleagues in adopting AI-enabled approaches, reproducible data workflows and practical coding practices.
• Lead cross-functional collaborations with Data Science, R&D IT and platform teams to deliver scalable solutions, align technical and scientific standards, and influence broader computational capabilities across Oncology R&D.
• Develop and apply agentic workflows to extract biological insight from high-dimensional datasets, including single-cell and spatial transcriptomics, functional screening data and multiomics integration.
• Stay current with advances in computational biology and AI methods, tools and best practices. Proactively evaluate and adopt fit-for-purpose approaches that strengthen discovery workflows.
• Prepare and deliver clear scientific and technical presentations within the Immune Cell Engagers Discovery group, across Oncology R&D and to relevant leadership audiences.
• Ensure compliance with internal standards and external regulations, and maintain accurate and timely records in the electronic laboratory notebook.

Skills

Python

R

AI architectures

Data engineering

Team leadership

Science communication

Education

PhD in relevant disciplines (Software Engineering, Computational Biology, Machine Learning, Data Science)

Tools

GitHub Copilot

Claude Code

Shiny

Domino

QuartzBio

Job description

AstraZeneca Cambridge is seeking an Associate Principal Scientist to lead AI-powered tools development for Oncology R&D. You will combine immunology and computational biology with data engineering to design scalable AI workflows and data platforms, partnering with wet-lab scientists and IT.

In this fixed-term role, you will provide technical leadership, build reusable software, mentor colleagues, and drive adoption of AI-enabled approaches across the discovery group, shaping the future of