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

Role Summary

Senior Data Scientist within AbbVie’s Operations Business Insights (OBI) group, responsible for building and overseeing predictive and prescriptive models using statistical and machine-learning methods. Will ensure end-to-end delivery of data science applications, studies, and proofs of concept, leading project teams of junior data scientists and analysts. Approximately 50% client-facing and 50% project involvement, with a focus on collaboration across Supply Chain, Manufacturing, Quality, Purchasing, and Science & Technology.

Responsibilities

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

Skills

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

Qualifications

• Required: Undergraduate with 6 years of experience, master‚Äôs with 5 years, or PhD in a related quantitative field (Data Science/Statistics/Predictive analytics or similar); preference for degrees in quantitative/engineering fields; experience in end-to-end data science project lifecycle including Agile; self-starter with adaptability; comfortable in a fast-paced, collaborative environment.
• Preferred: Experience in Quality, Manufacturing, or Central operations in a large pharmaceutical environment; knowledge of Factory 4.0/Smart Manufacturing trends; experience with technology transfer and innovation practices; familiarity with GxP systems; experience in MLOps/SLC in pharmaceutical operations; deep learning experience; experience with Apache Spark, TensorFlow, Keras; Linux/Unix familiarity; strong communication skills in English.