Data Scientist

What you'll do

• Compile, clean, and feature engineer laboratory and commercial data sets for multivariate and hybrid "Digital Twin" process models.
• Develop end-to-end data pipelines, products, and models from successful proofs of concept in collaboration with the Digital organization.
• Automate the process from data collection through model execution in a "Lab-in-the-Loop" environment.
• Formulate conclusions and design follow-on experiments based on multidisciplinary data.
• Initiate new areas of investigation that are scientifically meaningful and can be incorporated into research programs.
• Author publications, presentations, regulatory documents, and primary inventions for patents.
• Manage laboratory data and modeling capabilities while ensuring compliance with GxP standards and safety protocols.

What we're looking for

• A Bachelor's degree with 10 years of experience, a Master's degree with 8 years of experience, or a PhD is required.
• Candidates must possess a thorough theoretical and practical understanding of their own scientific discipline.
• Experience in biotech or pharmaceuticals is preferred.
• Strong experience in programming, including Python and SQL, is preferred.
• Experience with standard cloud-based data lake infrastructure and source code management tools like GitHub is preferred.
• Familiarity with data pipeline tools (KNime, dbt), model management tools (ML Flow, Databricks), or BI tools (Spotfire, PowerBI) is preferred.
• Experience with biotech data systems (AVEVA PI, LIMS, ELN, MES, ERP) and laboratory automation is preferred.
• Experience in SIMCA, JMP, or hybrid modeling is preferred.