Senior Data Scientist II

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

Group 

AbbVie Development Sciences (Dev Sci) is an integrated, cross-functional R&D organization that includes CMC (Process R&D, Drug Product Development and Analytical R&D), Biological Sciences (Preclinical Safety and Drug Metabolism, Pharmacokinetics & Bioanalysis) and Clinical Drug Supply Management functions responsible for the development of small molecule pharmaceuticals and therapeutic biologics from Discovery Candidate Selection through late stage clinical.  The Data & Digital Strategy CORE team within Development Sciences defines and executes our data and digital strategy in collaboration with Dev Sci subject matter experts and Information Research (IR).  The Data & Digital Strategy team partners cross-functionally to build and maintain a data and systems architecture that enables world-class knowledge management, data analytics and predictive modelling capabilities.  We are looking for diverse candidates with a blend of product development, informatics and data systems experience who can help advance our data and digital capabilities 

Purpose 

Conceive, design and implement new tools that solve significant scientific or business problems through the integration, visualization, and analysis of large and complex data. Work closely with science team to understand scientific needs, and generate new proposals based on those needs, and lead the efforts to bring the proposals to fruition. Investigate, identify, develop, and optimize new methods, algorithms, and technologies to derive novel, competitive insights from disparate data sources, or to drive productivity and efficiency gains. Act as a lead data scientist in area of expertise and critically eval