Applied R&D Data Scientist

This is a fully remote position, open to applicants in Oregon.

📋 Description

• Develop and implement machine learning, statistical, AI, and cheminformatics solutions to address R&D challenges in chemical synthesis, process development, analytical sciences, and bioconjugation.

• Convert both structured and unstructured scientific data into actionable insights, predictive models, and decision-support tools.

• Construct, validate, and enhance predictive and analytical models for reaction prediction, process optimization, impurity analysis, and experimental design.

• Design and assess AI-enabled capabilities such as generative AI, semantic search, information extraction, and scientific knowledge systems.

• Establish reproducible data pipelines, feature engineering workflows, and model evaluation frameworks.

• Maintain scientific integrity and ensure proper handling of uncertainty and model limitations.

• Collaborate with R&D scientists, chemists, process engineers, product managers, data engineers, and IT teams.

• Independently drive projects from problem definition to validated outcomes.

• Contribute to Lonza’s data science and AI capabilities within Advanced Synthesis.

⛳️ Requirements

• Bachelor's or master’s degree in data science, Computer Science, Statistics, Cheminformatics, Computational Chemistry, Chemistry, Engineering, or a related quantitative field; advanced degrees are preferred.

• Proven experience in applying data science, machine learning, AI, or scientific computing techniques to complex real-world scientific or technical issues.

• Strong programming proficiency in Python.

• Expertise with scientific computing and machine learning libraries such as pandas, NumPy, scikit-learn, PyTorch, or equivalent tools.

• Familiarity with chemistry and chemical data, including chemical structures, reactions, properties, and experimental datasets.

• Experience in developing, validating, and interpreting predictive models.

• Ability to effectively communicate results, assumptions, uncertainty, and limitations.

• Capability to work independently in ambiguous technical environments, identify practical solutions, and deliver high-quality outcomes with scientific rigor.

• Strong collaboration and communication skills across multidisciplinary teams.

• Ability to engage both technical and non-technical stakeholders.

🏝️ Benefits

• Performance-related bonus.

• Medical, dental, and vision insurance.

• 401(k) matching plan.

• Life insurance.

• Short-term and long-term disability insurance.

• Employee assistance programs.

• Paid time off (PTO).