remote
Scientist III, Data Scientist - Bioprocess Digital Twin - ThermoFisher Scientific
Data Scientist
Lead the design and implementation of digital twin models for bioprocesses, applying machine learning and statistical techniques in Python on cloud platforms to optimize manufacturing performance and support data‑driven decision making.
About the role
Key Responsibilities
- Develop and maintain high‑fidelity digital twin simulations of bioprocess workflows using Python, statistical modeling, and domain‑specific engineering knowledge.
- Apply machine‑learning algorithms to process data for predictive analytics, anomaly detection, and real‑time optimization.
- Integrate digital twin solutions with cloud infrastructure (e.g., AWS) to enable scalable data pipelines and collaborative research.
- Design interactive visualizations and dashboards that communicate model insights to cross‑functional teams.
- Collaborate with bioprocess engineers, software developers, and data scientists to translate scientific requirements into robust computational models.
Requirements
- Advanced degree (M.S. or Ph.D.) in Chemical Engineering, Bioengineering, Computer Science, or a related field.
- 5+ years of experience in data science, machine learning, or statistical modeling applied to bioprocess or manufacturing domains.
- Proficiency in Python and its data‑science ecosystem (pandas, scikit‑learn, TensorFlow/PyTorch).
- Hands‑on experience building and deploying models on cloud platforms, preferably AWS.
- Strong understanding of bioprocess engineering concepts and the ability to translate them into computational models.
Skills
pythonmachine learningaws