Senior Expert / Senior Principal PKS Data Scientist & Scientific Software Engineer (Dual level posting)

Act as a senior Modeling & Simulation Data Science representative on discovery and lead optimization programs, contributing scientific and strategic input to project discussions and decisions, and helping shape data science direction across programs. Partner with Data & Digital and PKS wet- and dry-lab teams to identify priority gaps, clarify business needs, and translate them into strategically aligned analytical and computational solutions with broad scientific and operational impact. Design, build, and maintain scalable applications, workflows, and data pipelines that support scientific analysis and decision making across projects and modalities. Develop, evaluate, and deploy machine learning and statistical models to uncover relationships between chemical structure and molecular or pharmacokinetic properties. Apply data mining, visualization, and exploratory analysis to derive insight from complex experimental datasets and communicate findings clearly to diverse stakeholders. Create and implement project- or modality-specific in silico models and data strategies that accelerate and streamline compound progression decisions while informing broader scientific direction and capability development. Write production-quality code following strong software engineering practices, including version control, testing, documentation, and maintainability standards. Lead and shape cross-functional initiatives across data science, software engineering, and laboratory teams, driving strategic alignment and organizational impact. Promote and champion the broad adoption of in-house tools, applications, and data science methods, helping shape best practices and strengthen data science capabilities across Translational Medicine and PKS. Stay current with advances in AI/ML, statistics, and computational methods relevant to ADME, PK/PD, and drug discovery, and proactively evaluate and bring appropriate innovation into practice to improve efficiency and scientific impact.

The Senior Data Scientist & Scientific Software Engineer will join the Modeling & Simulation Data Science team within the Translational Medicine Unit to help advance data-driven drug discovery. This role sits at the center of efforts to unlock the value of these data for decision making and to shape the future of medicine through advanced data science.

• Advanced degree in a relevant scientific or quantitative field such as cheminformatics, bioinformatics, biomedical engineering, computational biology, computational chemistry, AI/ML in life sciences, or a related discipline.

• PhD with 5+ years or MSc with 8+ years of relevant work experience applying data science in drug discovery, translational research, or related scientific environments, with a track record of leading complex initiatives and influencing scientific direction.

• Strong expertise in machine learning, statistics, and reproducible data science workflows, with demonstrated ability to apply them to complex scientific problems and guide others in their effective use.

• Proficiency in Python and/or R, with solid software development practices including version control, testing, documentation, and production-quality coding standards.

• Experience designing, developing, and deploying robust analytical applications, computational workflows, or machine learning systems, including shaping reusable solutions and technical direction in collaborative environments.

• Demonstrated ability to work across multidisciplinary teams, influence stakeholders, and translate complex analytical concepts into clear, actionable insights for scientists, partners, and leaders.

• Strong communication, collaboration, and leadership capabilities, with demonstrated ability to influence decisions and help shape direction in cross-functional settings.

• Excellent understanding of drug discovery processes, with particular relevance to ADME, pharmacokinetics, pharmacodynamics, or related translational data domains, and ability to articulate the impact and value of data science in strategic terms.