Applied R&D Data Scientist: AI for Life Sciences

Lonza; United States; On-site; Confidential; Full time

Benefits offered by this job

Medical, dental and vision insurance

401(k) matching plan

Life insurance and disability cover

Employee assistance programs

Paid time off

Job summary

Lonza is seeking an Applied R&D Data Scientist to translate complex scientific data into AI-enabled solutions that accelerate innovation in life sciences. You will apply machine learning, data science, and cheminformatics to solve R&D challenges and influence scientific decisions across a global organization.

Responsibilities include developing predictive models, transforming data into insights, and collaborating with chemists, engineers, and PMs to deliver impactful solutions and grow Lonza's

Qualifications

• Degree in a quantitative or scientific field with data science experience.
• Experience applying ML/AI to chemistry or pharma problems.
• Proficient Python and ML libraries (pandas, NumPy, scikit-learn, PyTorch).
• Ability to work independently in ambiguous environments and communicate results.

Responsibilities

• Develop ML and cheminformatics solutions for R&D challenges across synthesis and analytics.
• Transform data into actionable insights, models, and decision-support tools.
• Build and optimize predictive and analytical models for reactions, processes, and design.
• Design AI capabilities like generative AI, semantic search, information extraction.
• Create reproducible data pipelines and model evaluation frameworks with rigor.
• Collaborate with scientists and engineers to deliver solutions.

Skills

Python

Machine Learning

Data Science

Team collaboration

Education

Bachelor's or higher in quantitative/scientific field

Tools

pandas

NumPy

scikit-learn

PyTorch

Job description

Lonza is seeking an Applied R&D Data Scientist to translate complex scientific data into AI-enabled solutions that accelerate innovation in life sciences. You will apply machine learning, data science, and cheminformatics to solve R&D challenges and influence scientific decisions across a global organization.

Responsibilities include developing predictive models, transforming data into insights, and collaborating with chemists, engineers, and PMs to deliver impactful solutions and grow Lonza's