Data Scientist

About This Role

This is an exciting opportunity to work on a cross-functional team preparing data and enabling modeling activities in support of Product Development and Manufacturing Sciences organizations. The objective is to partner with modeling SMEs and the Digital organization to prepare data from source systems and data lakes, and enable model execution for statistical, hybrid and mechanistic models, with the ultimate objective to streamline and automate the process from data collection through model execution in a “Lab-in-the-Loop” environment.

Responsibilities

• Partner with Manufacturing Sciences to compile, clean and feature engineer laboratory and commercial data sets for multivariate and hybrid “Digital Twin” process models
• Partner with the Digital organization to deliver end-to-end data pipelines, products, and models from successful proofs of concept
• Routinely demonstrate scientific initiative and creativity in research or development activities
• Be highly autonomous and productive in performing laboratory research or method development, requiring only minimal direction from or interaction with supervisor
• Formulate conclusions and design follow-on experiments based on multidisciplinary data
• May initiate new areas of investigation that are scientifically meaningful, reliable, and can be incorporated directly into a research or development program
• Be a primary author of publications, presentations, regulatory documents and/or primary inventor of patents
• Demonstrate high proficiency across a wide range of relevant technologies
• Understand and adhere to corporate standards regarding code of conduct, safety, appropriate handling of materials, controlled drug and radioactive compounds, GxP compliance, and animal care where applicable

Requirements

• Bachelor’s Degree or equivalent education and typically 10 years of experience, Master’s Degree or equivalent education and typically 8 years of experience, PhD and no experience necessary
• Possess thorough theoretical and practical understanding of own scientific discipline
• Prior experience in biotech or pharmaceuticals

Nice to have:

• Masters in Data Engineering, Data Science or related
• Strong experience in programming, including Python, SQL, etc.
• Experience with standard cloud-based data lake infrastructure
• Experience using source code management tools (e.g. GitHub)
• Familiarity with data pipeline tools such as KNime, dbt, etc.
• Familiarity with model management and pipeline tools (ML Flow, DataBricks, etc.)
• Familiarity or willingness to learn ServiceNow and support application owner and access review for data and modeling capabilities
• Experience with biotech data systems (AVEVA PI, LIMS, ELN, MES, ERP, etc.)