Data Science Intern

Lonza • Vacaville, CA

12h • $26 - $38 • Onsite

About The Position

We are actively recruiting candidates to participate in our 2026 On-site Internship program. This position is 12 weeks in length and will immerse you in the culture and operations of Lonza Vacaville. The internship begins in May/June and ends in August. Potential interns must be able to commit to at least 40 hours per week throughout the summer. We are seeking a motivated Data Science Intern to join our Data Sciences and Innovation team. This internship offers a unique opportunity to work at the intersection of bioprocessing, advanced analytics, and machine learning. The successful candidate will contribute to developing predictive models that enhance process understanding and control in mammalian cell culture manufacturing.

Requirements

• Completion of junior year (typically 90 credits) towards a B.S. degree in Data Science, Computer Science, Chemical Engineering, Bioinformatics, or a related field.
• Must currently be enrolled in BS or MS Academic Program.
• Minimum cumulative GPA of 3.0 (out of 4) required.
• Proficiency in scripting languages (e.g., Python or R), and data querying languages (e.g., SQL).
• Expertise in ML, statistical modeling, and multivariate analysis, with a strong background in data pre-processing, experimentation, and visualization.
• Strong analytical and problem-solving skills, with the ability to communicate technical findings clearly to non-technical stakeholders.

Nice To Haves

• Knowledge of spectroscopy or bioprocessing concepts, and statistical software (e.g., JMP or SIMCA) is a plus.

Responsibilities

• Develop machine learning models using Process Analytical Technology (PAT) measurements, i.e., Raman Spectroscopy data, for cell culture process monitoring and control.
• Assess model performance for multiple cell culture metabolites (i.e., glucose, lactate, etc.) and evaluate model generalizability and robustness across various products and processes.
• Architect efficient and modularized pipeline for high-dimensional data transformation, feature engineering and selection, and model training.
• Explore predictive modeling approaches for Critical Quality Attributes (CQAs) that could be monitored and/or controlled in the upstream production bioreactor.
• Summarize findings and provide recommendations for future validation and implementation strategies.
• Collaborate with process scientists, data engineers, and manufacturing teams to ensure alignment with operational needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern