Senior Engineer, Process Data Science and Statistics
Core
Develop analytical workflows for multivariate process monitoring, predictive modeling of batch outcomes, and anomaly detection on high-dimensional process data for cell therapy manufacturing.
Role type
Senior IC process data scientist and statistical engineer
Builds
Data systems, analytical platforms, AI-enabled tooling, and interactive dashboards connecting process characterization and manufacturing execution data to decision support
Domain
Biopharmaceuticals / Cell Therapy / Manufacturing / Data Science
Deliverable
production ML models
Required skills
Multivariate statistical analysis, Python (pandas, scipy, statsmodels, scikit-learn), SQL, Predictive modeling, DOE design and analysis, Software development practices, Anomaly detection, Process capability analysis
Preferred skills
Cloud data systems (AWS, Snowflake, Databricks), Interactive analytical applications (Streamlit, Dash), Hybrid mechanistic and data-driven modeling, Neural ODEs, Agentic AI applications, Cell therapy or biologics manufacturing experience
Technologies
Python, SQL, pandas, scipy, statsmodels, scikit-learn, plotly, Snowflake, Streamlit, AWS, Databricks
Responsibilities
Design and analyze DOE studies for process characterization; Develop and maintain statistical control charts and multivariate SPC capabilities; Build predictive models linking incoming material attributes to batch outcomes; Develop and evaluate anomaly detection methods for high-dimensional process data; Build structured interactive reports and dashboards for batch visibility; Partner with IT to implement data pipelines and analytical platforms; Develop and evaluate hybrid mechanistic and data-driven models; Build reproducible AI/ML workflows with emphasis on explainability; Contribute to digital manufacturing capability development and mentor scientists and engineers
Seniority
Senior, hands-on IC with mentorship