Applied R&D Data Scientist
Join Lonza's Advanced Synthesis division and help transform scientific data into powerful AI-enabled solutions that accelerate innovation in life sciences. This is an exciting opportunity to apply machine learning, data science, and cheminformatics expertise to solve complex R&D challenges and influence how scientific decisions are made across a global organization.
What you will get:
A competitive compensation. In addition, below you will find a comprehensive summary of the benefits package we offer:
Performance-related bonus.
Medical, dental and vision insurance.
401(k) matching plan.
Life insurance, as well as short-term and long-term disability insurance.
Employee assistance programs.
Paid time off (PTO).
Compensation for this role will be determined by the candidate’s qualifications, skills, experience, and relevant knowledge.
What you will do:
Develop and apply machine learning, statistical, AI, and cheminformatics solutions to address high-priority R&D challenges across chemical synthesis, process development, analytical sciences, and bioconjugation.
Transform structured and unstructured scientific data into actionable insights, predictive models, and decision-support tools that enhance scientific understanding and experimental efficiency.
Build, validate, and optimize predictive and analytical models for applications such as reaction prediction, process optimization, impurity analysis, and experimental design.
Design and evaluate innovative AI-enabled capabilities, including generative AI, semantic search, information extraction, and scientific knowledge systems.
Create reproducible data pipelines, feature engineering workflows, and model evaluation frameworks while ensuring scientific rigor and appropriate treatment of uncertainty and model limitations.
Collaborate closely with R&D scientists, chemists, process engineers, product managers, data engineers, and IT teams to deliver impactful technical solutions and support implementation.
Drive projects independently from problem definition through to validated outcomes, contributing to the growth of Lonza’s data science and AI capabilities within Advanced Synthesis.
What we are looking for:
Bachelor's or master’s degree in data science, Computer Science, Statistics, Cheminformatics, Computational Chemistry, Chemistry, Engineering, or a related quantitative discipline. Advanced degrees are preferred.
Demonstrated experience applying data science, machine learning, AI, or scientific computing methods to solve complex real-world scientific or technical problems.
Strong programming skills in Python and proficiency with scientific computing and machine learning libraries such as pandas, NumPy, scikit-learn, PyTorch, or similar tools.
Working knowledge of chemistry and chemical data, including familiarity with chemical structures, reactions, properties, and experimental datasets.
Experience developing, validating, and interpreting predictive models while effectively communicating results, assumptions, uncertainty, and limitations.
Proven ability to work independently in ambiguous technical environments, identify practical solutions, and deliver high-quality outcomes with scientific rigor.
Strong collaboration and communication skills, with the ability to work effectively across multidisciplinary teams and engage both technical and non-technica