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# R&D Data Scientist

- **Company:** Lonza, Inc.
- **Location:** Bend, OR, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Programming, Information Extraction, Python (Programming Language), Machine Learning, NumPy, Scientific Computating, Search Technologies, Feature Engineering, Pytorch, Model Validation, Generative AI, Pandas, Scikit Learn, Data Pipelines, Software Library
- **Published:** September 4, 2026
- **Apply:** https://www.dice.com/job-detail/92c8d15a-db53-4f9f-b7e5-5d4f868f78fd

## About the Role

* Bachelor?s or advanced degree in a relevant quantitative or scientific discipline, with demonstrated experience applying data science or machine learning to chemistry, molecular, pharmaceutical, or related scientific R&D problems.
 * 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-technical stakeholders.

## Description

* 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.


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