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# MSAT Scientist - Data Analyst

- **Company:** Lonza, Inc.
- **Location:** Vacaville, CA, United States
- **Salary:** $95,250.0 - $158,750.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Information Engineering, Data Governance, Data Integrity, Extract Transform Load (ETL), Data Visualization, R (Programming Language), Python (Programming Language), Laboratory Information Management Systems, Machine Learning, Power BI, SAP (Applications), SQL Databases, Tableau (Software), Technical Data Management Systems, Yield Optimization
- **Published:** August 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fbdd953eb3ad01dd

## About the Role

* Bachelor's or advanced degree in scientific/life sciences/engineering field.
 * Strong proficiency in Python, R, SQL, and data visualization tools (Power BI, Tableau)
 * Expertise in statistical modeling, machine learning, and multivariate analysis
 * Familiarity with GMP-compliant environments and manufacturing systems (SAP, OSIsoft PI, MES)
 * Excellent problem-solving and communication skills
 * Ability to work collaboratively across technical and operational teams.

## Description

This is a fully site-based role. Working together in person supports close, real-time collaboration and the technical precision needed to manufacture medicines to the highest quality and safety standards.

MSAT Scientist - Data Analyst will support the development and deployment of advanced data products and analytics solutions to support biologics manufacturing operations. This role will assist strategic initiatives, and influencing site-level digital transformation. The candidate will apply technical expertise in data engineering, statistical modeling, and bioprocessing to optimize manufacturing performance and ensure data integrity in GMP environments., * Support the design and implementation of predictive models for process optimization, deviation detection, and yield improvement.

 * Analyze manufacturing data from systems such as LIMS, MES, and PAT using statistical and machine learning techniques.
 * Collaborate with manufacturing, process development, and quality teams to develop high-impact data products using batch records, process parameters, alarms, and time-series data.
 * Assist with maintaining robust ETL pipelines and data schemas to support scalable analytics
 * Ensure compliance with GMP, data governance, and regulatory standards.
 * Prototype emerging technologies (e.g., Raman spectroscopy, RAG, generative AI) for manufacturing applications.
 * Contribute to the development of site-level digital strategy.


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