remote
Scientist II, Data Scientist - Bioprocess Digital Twin
Data Scientist
Develop and maintain digital twin models of CHO cell bioprocesses, applying machine learning and statistical techniques to predict cell growth, viability, and productivity using Python and advanced data analytics.
About the role
Key Responsibilities
- Design, implement, and validate digital twin models for CHO cell culture bioprocesses.
- Apply machine‑learning algorithms to predict cell growth, viability, and product yield from multi‑omics and process data.
- Integrate real‑time sensor data and historical batch records into scalable modeling pipelines.
- Collaborate with bioprocess engineers to translate model insights into actionable process improvements.
- Document model architecture, assumptions, and performance metrics for regulatory and knowledge‑transfer purposes.
Requirements
- Advanced degree (M.S. or Ph.D.) in Bioengineering, Chemical Engineering, Computational Biology, or a related field.
- Proficiency in Python for data manipulation, statistical analysis, and machine‑learning model development.
- Strong background in bioprocess modeling, CHO cell culture, and quantitative analysis of cell growth and viability.
- Experience with data integration from laboratory instruments, high‑throughput assays, and process control systems.
- Excellent problem‑solving skills and ability to communicate complex model outcomes to cross‑functional teams.
Skills
pythonmachine learningdata analysis