Data Scientist

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About the 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 at AbbVie. Within the Product Development laboratories, 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.  This environment should enable end-to-end automation of laboratory data and modeling in a way that is accessible for all laboratory scientists to access. It should also provide an opportunity to gain a deep understanding of bioprocess data, and also to learn multivariate, hybrid and machine learning modeling in support of deeper scientific insights, and upholding the highest standards of quality and productivity.   Responsibilities: • Partner with Manufacturing Sciences, the objective is to compile, clean and feature engineer the same 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. • 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. • A primary author of publications, presentations, regulatory documents and/or primary inventor of patents. • Demonstrates 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. • 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   Preferred Qualifications: • 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 preferred (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 preferred: AVEVA PI, LIMS, ELN, MES, ERP, etc. • Experience with laboratory automation and data • Some experience with BI tools preferred (e.g. Spotfire, PowerBI, etc.) • Experience in SIMCA, JMP, or hybrid modeling preferred • Interest in learning, or experience with process, statistical, hybrid, mechanistic, and/or machine learning models. Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​ • The compensation range described below is the range of possible base pay compensation th

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