Data Scientist
Core
Apply statistical trending tools and engineering principles to product and method data to understand variation, evaluate improvements, and support GMP activities in biopharma process development.
Role type
Data Scientist (Process Development)
Builds
Analytical method performance visualizations, statistical analyses, and ML models for protein structure understanding
Domain
Biopharma / Process Development
Deliverable
production ML models | dashboards & analysis
Required skills
Statistical analysis, multivariate analysis, time series analysis, hypothesis testing, data pipeline development (ETL), Python, R, Power BI, Tableau, Databricks, Snowflake, Amazon Redshift, Machine Learning (classification, regression, anomaly detection), Deep Learning, NLP, Convolutional Neural Networks
Preferred skills
None stated
Technologies
Power BI, Tableau, Databricks, Snowflake, Amazon Redshift, Python, R
Responsibilities
Apply statistical trending tools to product and method data; Use data analytics software to develop visualizations to review, assess, and improve analytical method performance; Interface with analytical scientists, process development scientists, and engineers to assess, understand, and support data consumption needs; Interface with product quality, QC, quality assurance, and manufacturing organizations to resolve method issues; Support ongoing GMP activities such as the generation of the annual product review documents, regulatory inspections, and process documentation; Apply machine learning methodologies where appropriate for analyzing datasets.
Seniority
Mid-level (Master's degree + 1 year experience or equivalent project)