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

Role Summary

Senior Data Scientist in AbbVie’s Operations Business Insights (OBI) group focusing on predictive and prescriptive analytics across Supply Chain, Manufacturing, Quality, Purchasing and Science & Technology. Responsible for end-to-end delivery of data science applications and leading project teams of junior data scientists and analysts. Combines consulting and collaboration to drive data science opportunities with cross-functional partners; approximately 50% client-facing and 50% project work.

Responsibilities

• Operate cross-functionally with OBI data scientists, senior functional leaders and business partners.
• Consult with business users to analyze requirements and recommend solutions anticipating future impacts of changing requirements.
• Spearhead technology transfer of data science methods into functional areas and expand the footprint of impactful data science.
• Develop advanced data analytical models using supervised/unsupervised learning, statistics, and predictive modeling.
• Mentor and coach team members.
• Build relationships with stakeholders and collaborate with other statistical and data science teams.
• Collaborate with OBI academic partners and AbbVie Innovation Center on research projects and POCs.

Qualifications

• Required: Undergraduate with 6 years of experience, master’s degree with 5 years of experience, or PhD in a related quantitative field (Data Science/Statistics/Predictive analytics or similar). Preference for quantitative or engineering undergraduates in chemistry/chemical engineering, mathematics, or related industrial/engineering degrees.
• Required: Experience in full life-cycle of build, deploy, monitoring and evolution of complex data science applications including Agile project management.
• Required: Self-starter capable of aligning with changing requirements; quick to learn new tools and concepts relevant to stakeholder needs.
• Required: Comfortable working in a fast-paced, highly collaborative environment.
• Preferred: Experience in Quality, Manufacturing or Central operations in a large pharmaceutical environment.
• Preferred: Awareness of trends in Factory 4.0 or Smart Manufacturing in pharmaceutical operations.
• Preferred: Experience in technology transfer and innovation practices, GxP systems, MLOps/SLC in pharmaceutical operations, and Deep Learning models.
• Preferred: Experience with Apache Spark, TensorFlow, Keras; OS Linux/Unix familiarity.
• Preferred: Degree combinations as listed; strong written and oral English communication skills.

Skills

• Expert knowledge of statistical and machine learning methods, modeling and business analytics.
• Proficiency with data science tools (Knime, Dataiku, AWS SageMaker) and statistical languages (R, Python, Julia, SAS); data visualization (Tableau, ggplot, matplotlib, R/Shiny, Qlik); data manipulation (SQL, Spark, PySpark, Hive); cloud environments (Azure, AWS).
• Expertise in designing and developing processes to consolidate and analyze data (structured, unstructured, big data) with focus on data quality and velocity.
• Experience with missing data analysis, master data management, and good modeling preparation practices.
• Storytelling with data; ability to communicate complex topics to diverse audiences; capability to lead internal learning and education sessions.
• Effective communication to executive-level audiences.

Education

• Undergraduate with 6 years of experience, master’s degree with 5 years of experience, or PhD in a related quantitative field (Data Science/Statistics/Predictive analytics or similar).
• Preferences for degrees in chemistry/chemical engineering, mathematics, or related industrial/engineering disciplines.