AI-Driven R&D Data Scientist for Life Sciences

Lonza Group Ltd.; Bend (OR); Hybrid; Confidential; Full time

Benefits offered by this job

Performance bonus

Medical/dental/vision insurance

401(k) matching

Life insurance

Disability insurance

Employee assistance program

Paid time off

Job summary

Lonza Group Ltd. in Bend, Oregon, is seeking an Applied R&D Data Scientist to transform scientific data into AI-enabled solutions that accelerate life sciences innovation.

You will apply machine learning, data science, and cheminformatics to solve challenging R&D problems and inform scientific decisions across a global organization. This role builds predictive models for reaction prediction and process optimization, designs AI-enabled capabilities, creates reproducible data pipelines, and

Qualifications

• Degree in a quantitative or scientific field with data science/machine learning experience.
• Experience applying data science/ML methods to chemistry or related R&D problems.
• Strong Python and scientific computing library proficiency.

Responsibilities

• Develop and apply ML, AI, and cheminformatics solutions across R&D challenges.
• Transform structured/unstructured data into actionable insights and predictive models.
• Build and validate models for reaction prediction, process optimization, and design.
• Create reproducible data pipelines and evaluation frameworks with scientific rigor.

Skills

Python programming

Data science

Machine learning

Cheminformatics

Scientific computing

Communication

Education

Bachelor’s or advanced degree in a quantitative/scientific discipline

Tools

Pandas

NumPy

Scikit-learn

PyTorch

Job description

Lonza Group Ltd. in Bend, Oregon, is seeking an Applied R&D Data Scientist to transform scientific data into AI-enabled solutions that accelerate life sciences innovation.

You will apply machine learning, data science, and cheminformatics to solve challenging R&D problems and inform scientific decisions across a global organization. This role builds predictive models for reaction prediction and process optimization, designs AI-enabled capabilities, creates reproducible data pipelines, and