Senior Scientist, Research Informatics and Data Science

This role sits at the intersection of bioinformatics, software engineering, data science, laboratory automation, and AI. The successful candidate will partner closely with scientists, automation engineers, data scientists, and IT teams to develop robust, scalable, and user-centric solutions that improve data capture, automate workflows, and establish FAIR data foundations for AI-driven biologics discovery and development.

The position combines hands-on technical delivery with scientific partnership and will play a key role in enabling foundation builds, workflow automation, data products, and emerging AI capabilities across the Biologics Engineering ecosystem.

Key Responsibilities:

• Apply scientific informatics expertise to address complex challenges across bioinformatics and data science in laboratory environments.

• Translate biologics drug discovery workflows into automated processes, scalable digital products, and user-centred solutions that improve research efficiency and data quality.

• Integrate research systems by connecting laboratory instruments, automation platforms, FAIR data repositories, and scientific applications such as Genedata Biologics.

• Develop scientific software including applications, APIs, services, and user interfaces using

• Establish data foundations through reusable data models, metadata standards, and FAIR data products in Snowflake that support analytics, machine learning, and AI.

• Apply AI and agentic development practices to rapidly prototype tools and visualisation capabilities that enhance lead selection and decision-making in drug discovery campaigns.

• Collaborate across disciplines with scientists, automation engineers, product owners, AI specialists, and IT teams to deliver robust and impactful solutions.

We are seeking an experienced and highly motivated informatics and data science professional to accelerate the digital transformation of Biologics Engineering by building the data, software, and automation foundations that enable next-generation scientific workflows., * PhD, MSc, or equivalent industry experience in Bioinformatics, Data Science, Computer Science, Software Engineering, Computational Biology, Engineering, or a related discipline.

• Experience developing software solutions using Python and modern engineering practices.

• Experience designing data pipelines and integrating heterogeneous scientific data sources.

• Strong understanding of laboratory research environments and data generation workflows.

• Experience working directly with scientists and technical stakeholders to deliver real-world solutions.

• Demonstrated ability to translate ambiguous scientific needs into practical digital products.

Preferred Qualifications:

• Experience with laboratory automation platforms and instrument integrations.

• Knowledge of cloud-based data platforms and modern data engineering approaches.

• Experience developing APIs, workflow orchestration systems, or scientific web applications.

• Experience applying machine learning, generative AI, or advanced analytics in scientific environments.

• Familiarity with FAIR data principles and research data governance.

• Experience working within agile product teams.