Data Scientist II

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today!

Summary : At Cencora, data scientists work on high-impact problems at the intersection of healthcare, supply chain, operations, finance, and strategy. As a Data Scientist II, you will own small-to-medium analytics initiatives end-to-end — scoping problems, building solutions, and delivering results that stakeholders trust and act on. This role is ideal for someone who is ready to take ownership of projects with growing independence — translating business questions into analytical plans, executing with technical rigor, and communicating findings that influence real decisions. Success here is defined not just by technical quality, but by adoption, trust, and business impact.

Own end-to-end delivery of moderately complex analyses, models, and data products — from translating business questions into clear analytical plans through results delivery — defining success metrics, assumptions, and practical trade-offs along the way, with limited oversight. Explore, profile, and prepare structured and semi-structured datasets from internal and external sources. Build and maintain data pipelines — including extraction, transformation, and loading workflows — to support analytical and modeling workstreams. Design, build, validate, and iterate on statistical, forecasting, and machine learning solutions appropriate to the problem at hand. Conduct hypothesis-driven analysis, experimentation, and model evaluation. Deploy models into production environments, implement monitoring for model performance and data drift, and support ongoing model maintenance and retraining. Partner directly with business stakeholders on defined problems, building credibility and beginning to influence priorities through the quality of your insight. Communicate recommendations, assumptions, trade-offs, and business implications clearly to both technical and non-technical audiences. Write reusable, well-documented, production-quality code and uphold team standards for reproducibility, version control, responsible AI, and governance. What You Bring: A track record of independently delivering analytical work that drives business recommendations — not just technical outputs. The ability to translate a business question into an analytical approach and identify practical trade-offs along the way. Clear written and verbal communication skills, including comfort presenting findings to stakeholders and operational partners. Curiosity, ownership, sound judgment, and a drive to continuously learn — including seeking feedback, exploring new methods, and growing your domain expertise.

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field — or equivalent practical experience. 2+ years of professional experience in a data science, applied analytics, or quantitative modeling role (or equivalent depth through advanced education and applied projects). Proficiency in Python and SQL. Solid understanding of statistics, machine learning, and analytical problem solving, including experimentation and hypothesis testing methodologies. Experience with — or demonstrated aptitude for — data pipeline tools and model deployment/monitoring practices. Experience working with datasets of varying scale using common data processing libraries (e.g., pandas, PySpark). Ability to deliver analytical work with increasing independence, including contributing to problem framing, methodology selection, and communicating results. Proficiency with version control (e.g., Git) and writing