develop innovative predictive models that are reliable, scalable, and modular and drive to business relevant outcomes
work with stakeholders to define business questions, requirements, timelines, objectives, and success criteria for data science initiatives
serve as a key team member on the Advanced Data Science arm of the Global Winning with Data team, working in close partnership with the Digital Transformation and Wining with Data Global Commercial Capability teams and becoming a trusted partner to Global, Area and Affiliate leadership, ensuring data and digital strategy and key deliverables reflect advanced data science best practices
maintain, optimise, scale, and operationalize existing machine learning models in concert with key partners such as the Digital Transformation team, BTS, and external vendors/partners
utilise data sets of varying degrees of size and complexity and develop novel way to create creative predictive analytic solutions to work around data limitations
proactively identify new data science approaches that would improve our ability to answer commercial business questions by closely collaborate with key stakeholders to transform business questions to algorithms and further support the business needs
work closely with Business Technology Solutions colleagues to ensure smooth transition of pilots into production, including technical guidance with respect to replication and scaling
Requirements
BS degree required, with demonstration and focus in applied data science, in Statistics, Engineering, Operations Research, Computer Science or Economics
experience developing and executing data science to address key business questions with positive, measurable outcomes
experience analysing and drawing insights from key internally generated and external data sets
abbVie is an equal opportunity employer including disability/vets
desirable: Advanced degree in Statistics, Math, or Computing Science or equivalent practical experience
desirable: Expertise in other languages such as R, Java, C
experience of applied data science and fields such as data engineering and predictive modeling or strong academic background in Statistics, Mathematics, Physics, Computer Science or Computer Engineering