Product-Focused Data Scientist for AI-Powered Analytics

Cardinal Health; Pierre (SD); On-site; USD 94,900 - 122,040; Full time

Benefits offered by this job

Medical/Dental/Vision

Paid time off

HSA

401k

MyFlexPay

FSAs

Disability

Work-Life

Parental leave

Lifestyle programs

Job summary

Cardinal Health seeks a product-oriented Data Science professional who partners with engineering teams to turn analytical concepts into real, working business solutions. You will be hands-on with data — building prototypes, designing outputs, and setting up tracking metrics — but your primary focus is ensuring our products serve a clear business purpose.

You will act as the bridge between technical development and financial workflows, ensuring the models we build are trusted, highly usable, and

Qualifications

• 4-8 years of experience, preferred.
• Bachelor's degree in related field, or equivalent work experience, preferred.
• Strong proficiency in programming languages (SQL & Python).
• Experience working within Agile and SDLC frameworks.
• Experience using Git and CI/CD tools (e.g., GitHub Actions, GitLab, Azure DevOps, Jenkins).
• Experience containerizing applications and machine learning models using Docker.
• Experience deploying, managing, or supporting workloads on Kubernetes platforms.

Responsibilities

• Build prototypes and outputs, set up tracking metrics.
• Bridge between technical development and financial workflows.
• Ensure models are trusted, usable, and integrated into daily business processes.

Skills

SQL

Python

Agile methodologies

SDLC

Education

Bachelor's degree or equivalent

Tools

Git

CI/CD

Docker

Kubernetes

Job description

Cardinal Health seeks a product-oriented Data Science professional who partners with engineering teams to turn analytical concepts into real, working business solutions. You will be hands-on with data — building prototypes, designing outputs, and setting up tracking metrics — but your primary focus is ensuring our products serve a clear business purpose.

You will act as the bridge between technical development and financial workflows, ensuring the models we build are trusted, highly usable, and