Data Scientist - Supply Chain & Operations Research

Cardinal Health; Indianapolis (IN); On-site; USD 95,000 - 122,000; Full time

Benefits offered by this job

Health benefits

Time off

401k plan

Parental leave

Wellness programs

Job summary

Cardinal Health is seeking a Data Scientist, Operations Research Analyst to join the DS2 team to enhance our pharmaceutical supply chain performance. You will forecast demand, build optimization and simulation models, and communicate actionable insights across cross‑functional teams.

The role emphasizes applying quantitative methods to inventory, labor, transportation, and capacity planning, with collaboration across data engineers and business partners.

Qualifications

• 2–4 years of experience in data science or OR.
• Bachelor's degree in a quantitative field or equivalent work experience.
• MS/MBA with focus in Data Science, OR, IE, or Statistics preferred.
• Experience applying DS/OR techniques to logistics and supply chain problems.
• Experience with SQL and databases.
• Experience with R, Python, SQL, Alteryx, Tableau, and SAS.
• Experience with OR tools like AnyLogic or CPLEX.
• Excellent communication and ability to work in a team.

Responsibilities

• Apply DS and OR techniques to logistics and supply chain problems.
• Forecast future demand, build optimization and simulation models.
• Collaborate with cross‑functional teams to implement solutions.
• Develop prescriptive models using software and custom code.
• Explain results in clear business terms to stakeholders.

Skills

SQL

R

Python

Tableau

SAS

AnyLogic

CPLEX

Operations Research

Education

Bachelors degree

MS/MBA focus

Tools

AnyLogic

CPLEX

Job description

Cardinal Health is seeking a Data Scientist, Operations Research Analyst to join the DS2 team to enhance our pharmaceutical supply chain performance. You will forecast demand, build optimization and simulation models, and communicate actionable insights across cross‑functional teams.

The role emphasizes applying quantitative methods to inventory, labor, transportation, and capacity planning, with collaboration across data engineers and business partners.