Senior Scientist, Data I (Chemistry, Materials Controls – Acceleration)

AbbVie’s Operations Business Insights (OBI) group is continuously innovating to transform AbbVie operations organization to enable the use of data and analytics to drive world-class innovation, performance, and agility in service of our patients across the globe. We are looking for a Senior Data Scientist with wide-ranging analytics experience to work within a diverse operations business which includes Supply Chain, Manufacturing, Quality, Purchasing and Science & Technology. The Senior Data Scientist will build and oversee the building of predictive/prescriptive models using statistical and machine-learning methodologies. The Senior Data Scientist will also ensure end-to-end delivery of assigned data science applications, studies and POCs overseeing project teams of junior data scientists and data analysts. This role will also serve as a key contributor and thought leader to the group strategy, awareness/education activities and discovery/development/ideation of data science opportunities in the various functional areas OBI serves. This role will operate about 50% client-facing and 50% project involvement. Consulting and collaboration skill set is key to success in this role. This is a demanding role with highly visible impact to senior leaders across the operations context.

ResponsibilitiesOperate cross-functionally in collaboration with OBI functionally-aligned data scientists, senior functional leaders and business partners. Consult with business users in the analysis of requirements and recommend solutions which anticipate the future impact of changing business requirements. Seek, develop, and implement opportunities for technology transfer of data science methods into functional areas – spearheading the use of new methods and expanding the footprint of impactful data science. Develop advanced data analytical models and techniques from supervised and unsupervised machine learning, statistical analysis, and predictive modeling. Mentor and coach related team members Build relationships with stakeholders and collaborate with other statistical and data science teams in AbbVie. Collaborate with OBI academic partners and AbbVie Innovation Center on research projects and POCs Detailed expectations include (but not limited to ) : Position requires a high degree of communication and collaboration with functional and business partners. Role is expected to maintain and execute practice roadmaps in alignment with functional partners and business partners at multi-year, annual and quarterly timescales. Role is expected to maintain consulting, educational and briefing materials commensurate with the evolution of architecture, design, project status, and best practices for the practice/functional area and to collaborate on overall team materials. Role is expected to devise and operate an effective communication plan with key stakeholders. Role is expected to demonstrate thought leadership through proposals and planning for current and future state needs. Role is expected to quickly assess new opportunities (AI/ML techniques, technology, etc.) and present these within the current and future state of requirements, risk and cost-effectiveness. Role is expected to perform requirements discovery, determine feasibility of various approaches, devise experimental approaches to test assumptions and devise solutions which incorporate non-functional requirements such as scalability, interpretability, and maintainability. Role will be expected to drive one or more key internal initiatives such as cross-functional GenAI development, data science platform evolution or operations-wide MLOps / governance / methodology / SLC updates appropriate for AI/ML in addition to planned and ad hoc functional initiatives. Tools and skills you will use: Expert knowledge of statistical and machine learning methods, with expertise in modeling and business analytics Data Science tools like Knime, Dataiku, AWS SageMaker, statistical languages and packages, e.g., R, Python, Julia, SAS, data visualization tools and techniques, e.g. Tableau, ggplot, matplotlib, R/Shiny, Qlik, Data manipulation tools such as SQL, Spark, PySpark and Hive, cloud environments like Azure and AWS Expertise in designing and developing processes and systems to consolidate and analyze data. Considerations include variety (structured, unstructured), volume (includes big data), data quality (cleaning and validation of the data) and velocity (batch, stream). Expertise in processes / procedures for missing data analysis, data quality, master data management and good preparation practices for modeling. Expertise in story-telling with data and communicating complex topics to audiences of all levels Able to drive internal learning through journal clubs, internal data science education sessions and continuously deepen the team knowledge in data science practice and research. Able to communicate effectively to an executive level audience.