Data Scientist

What you'll do

• Compile, clean, and feature engineer laboratory and commercial data sets for multivariate and hybrid process models.
• Deliver end-to-end data pipelines, products, and models from successful proofs of concept.
• Prepare data from source systems and data lakes to enable model execution for statistical and mechanistic models.
• 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.
• Author publications, presentations, regulatory documents, and primary inventions for patents.
• Perform laboratory research and method development with high autonomy and minimal supervision.

What we're looking for

• Bachelor’s Degree with 10 years of experience, Master’s Degree with 8 years of experience, or a PhD with no experience required.
• Thorough theoretical and practical understanding of own scientific discipline.
• Prior experience in biotech or pharmaceuticals.
• Master’s in Data Engineering, Data Science, or related field (preferred).
• Strong experience in programming, including Python and SQL (preferred).
• Experience with cloud-based data lake infrastructure, source code management tools like GitHub, and data pipeline tools like KNime or dbt (preferred).
• Experience with biotech data systems, laboratory automation, and BI tools like Spotfire or PowerBI (preferred).
• Experience in SIMCA, JMP, or hybrid modeling (preferred).