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 sets are key to success in this role. This is a demanding role with highly visible impact to senior leaders across the operations context.

　　Primary Responsibilities/Duties

　　Operate cross-functionally in a highly collaborative manner 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, deep learning and predictive modeling.

　　Build relationships with stakeholders and collaborate with other statistical and data science teams in AbbVie while mentoring and coaching related team members

　　Collaborate with academic partners and AbbVie Innovation Center on research projects and POCs

　　Detailed expectations include (but not limited to):

　　Maintain and execute practice roadmaps in alignment with functional partners and business partners at multi-year, annual and quarterly timescales.

　　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.

　　Devise and operate an effective communication plan with key stakeholders.

　　Demonstrate thought leadership through proposals, white papers, architectural inputs 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.

　　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.

　　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 in this role:

　　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, deep learning tools such as Tensorflow, Keras and PyTorch

　　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.

　　Experiences that make you a strong candidate for this role:

　　Required

　　Undergraduate with 7 years of experience, master’s degree with 6 years of experience, or PhD in a related quantitative field with 2 years of experience, in a non-academic setting - Data Science/Statistics/Predictive analytics or similar. For advanced degree holders, preference is for quantitative or engineering undergraduates such as chemistry/chemical engineering, mathematics, other industrial / engineering degrees.

　　Experience in full life-cycle and evolution of complex data science applications including Agile Project management processes

　　Self-learner able to quickly become effective in new tools, concepts, and academic findings relevant to OBI/stakeholder needs.

　　Beneficial

　　Experience in Quality, Manufacturing or Central Operations context in a large pharmaceutical environment including GxP systems and processes.

　　Awareness or experience in key industry trends in related areas such as ‘Factory 4.0’ or ‘Smart Manufacturing’ in pharmaceutical manufacturing operations.

　　Experience in technology transfer and innovation practices through consulting experience or through corporate roles supporting these practices.

　　Experience in MLOps/SLC in Pharmaceutical operations.

　　If you believe you’re a great fit for this job but don’t have all of the experiences listed above, we encourage you to apply anyway!

　　Why Business Technology Solutions

　　For anyone who wants to use technology and data to make a difference in people’s lives, shape the digital transformation of a leading biopharmaceutical company, and secure sustainable career growth within a diverse, global team: we’re ready for you.

　　The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.

　　We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.

　　This job is eligible to participate in our short-term incentive programs.

　　This job is eligible to participate in our long-term incentive programs.

　　Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.

　　AbbVie is committed to operating with integrity, driving innovation, transforming lives, serving our community, and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.