Senior Data Analyst, Data Analytics

Cardinal Health•Dublin, OH

About The Position

What Data Analytics contributes to Cardinal Health: The Data & Analytics Function oversees the analytics life-cycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage. This function manages analytic data platforms, the access, design and implementation of reporting/business intelligence solutions, and the application of advanced quantitative modeling. As a Data Analyst with AI expertise, you will apply business process knowledge, analytics, and emerging AI capabilities to deliver timely, accurate, and actionable insights. You will partner closely with cross‑functional teams to build models, dashboards, automations, and decision‑support tools that enhance performance, efficiency, and responsiveness across the business. This role is ideal for someone who thrives at the intersection of analytics, automation, and applied AI—and who is excited to shape how our organization leverages data to gain competitive advantage.

Requirements

Bachelor’s degree in a related field preferred (e.g., Data Science, Analytics, Statistics, Computer Science, Business) or equivalent experience
8–12 years of experience in analytics, business intelligence, or a related field preferred
Strong proficiency in SQL and at least one analytics or automation tool (e.g., Alteryx, Python, R).
Experience with AI/ML concepts and tools (e.g., scikit‑learn, TensorFlow, Azure ML, or similar).
Demonstrated ability to translate business questions into analytical solutions.
Experience building dashboards and visualizations using Tableau, Looker, Power BI, or similar tools.
Excellent communication, collaboration, and project management skills.
Ability to work independently on complex, high‑impact projects with minimal guidance.

Responsibilities

Develop and maintain dashboards, scorecards, and data visualizations using tools such as Tableau, Power BI, or similar platforms.
Use SQL, Alteryx, Python, or other analytics tools to manage, transform, and analyze complex datasets.
Apply AI/ML techniques (e.g., predictive modeling, clustering, NLP, forecasting) to support business decision‑making and uncover new opportunities.
Automate manual processes and build scalable, repeatable data workflows that improve efficiency and data quality.
Collaborate with cross‑functional partners to gather requirements, translate business needs into analytical solutions, and adapt to shifting priorities.
Communicate insights clearly and effectively to technical and non-technical stakeholders through presentations, reports, and data storytelling.
Contribute to the design and enhancement of data platforms, analytics processes, and governance practices.
Mentor junior analysts and support the development of best practices across the analytics team.