Senior Data Scientist - Operation Research

Tiger Analytics; Wisconsin; On-site; USD 95,000 - 122,000; Full time

Benefits offered by this job

Medical insurance

401k plan

HSA

Paid time off

MyFlexPay access

Job summary

Cardinal Health is seeking a Senior Data Scientist Operations Research to identify business problems with clients and develop data-driven solutions. The role focuses on predictive modeling, optimization, and prescriptive analytics to improve supply chain performance.

You will work with data engineers and cross-functional teams to design models, evaluate alternatives, and communicate financial and operational impacts. Some travel may be required.

Qualifications

• 2–4 years of experience, preferred.
• Bachelor’s degree in a quantitative field, or equivalent work experience, preferred.
• MS/MBA with focus in Data Science, Operations Research, Industrial Engineering, or Statistics preferred.
• Demonstrated ability to apply Data Science and Operations Research techniques to logistics and supply chain management problems preferred.
• Experience with Structured Query Language (SQL) and working with databases preferred.
• Experience with data analysis tools such as R, Python, SQL, Alteryx, Tableau, and SAS preferred.
• Experience with Strategic Network Design, Simulation (e.g. AnyLogic), or Mathematical Programming (e.g. CPLEX) software preferred.
• Ability to travel up to 5%.

Responsibilities

• Listen to clients and ask questions to clearly define business problems.
• Perform exploratory analysis to determine root causes of problems and confirm/disprove hypotheses.
• Develop predictive models to forecast future volumes that will drive capacity/resource needs.
• Develop customer and product segmentation models and design our supply chain to support differentiated services.
• Build optimization and simulation models to recommend capacity investments, resource plans, policy changes, and process changes to improve supply chain performance.
• Develop prescriptive models using 3rd party optimization/simulation software and custom-built models.
• Recommend solutions. Summarize the financial and operational impact of the recommendation and pros/cons of alternatives considered.
• Work with Data Engineers to create data models for analyses.

Skills

SQL

Python

R

Tableau

SAS

AnyLogic

CPLEX

Education

MS/MBA in Data Science/OR/Industrial Eng/Statistics

Bachelors in quantitative field

Tools

AnyLogic

CPLEX

Alteryx

Tableau

Job description

Senior Data Scientist Operation Research – Cardinal Health

Cardinal Health’s Data and 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. Data Science applies baseline, scientific methodologies from various disciplines, techniques and tools that extracts knowledge and insight from data to solve complex business problems on large data sets, integrating multiple systems.

Key Responsibilities

• Listen to clients and ask questions to clearly define business problems.
• Perform exploratory analysis to determine root causes of problems and confirm/disprove hypotheses.
• Develop predictive models to forecast future volumes that will drive capacity/resource needs.
• Develop customer and product segmentation models and design our supply chain to support differentiated services.
• Build optimization and simulation models to recommend capacity investments, resource plans, policy changes, and process changes to improve supply chain performance.
• Develop prescriptive models using 3rd party optimization/simulation software and custom-built models.
• Recommend solutions. Summarize the financial and operational impact of the recommendation and pros/cons of alternatives considered.
• Work with Data Engineers to create data models for analyses.

Qualifications

• 2-4 years of experience, preferred.
• Bachelor’s degree in a quantitative field, or equivalent work experience, preferred.
• MS/MBA with focus in Data Science, Operations Research, Industrial Engineering, or Statistics preferred.
• Demonstrated ability to apply Data Science and Operations Research techniques to logistics and supply chain management problems preferred.
• Experience with Structured Query Language (SQL) and working with databases preferred.
• Experience with data analysis tools such as R, Python, SQL, Alteryx, Tableau, and SAS preferred.
• Experience with Strategic Network Design, Simulation (e.g. AnyLogic), or Mathematical Programming (e.g. CPLEX) software preferred.
• Ability to work as part of a team as the key analytical resource.
• Excellent communication skills with an ability to explain quantitative analysis in simple business terms.
• Intellectual curiosity, humility, genuine respect and desire to help others.
• Bias for action and passion for driving change.
• Ability to travel up to 5%.

Salary and Benefits

Anticipated salary range: $94,900 - $122,000

Bonus eligible: No

Benefits:

• Medical, dental and vision coverage.
• Paid time off plan.
• Health savings account (HSA).
• 401k savings plan.
• Access to wages before pay day with myFlexPay.
• Flexible spending accounts (FSAs).
• Short- and long-term disability coverage.
• Work-Life resources.
• Paid parental leave.
• Healthy lifestyle programs.

Application Window & EEO Statement

Application window anticipated to close: 11/2/2026.

Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.