Data Scientist Intern: Healthcare Analytics & Supply Chain

MWI Animal Health; Conshohocken (Montgomery County); On-site; USD 28,000 - 41,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision care

Paid parental leave

Mentorship programs

Professional development resources

Volunteer activities

Job summary

Cencora is seeking a Data Scientist Intern to explore data, build models, and contribute to data pipelines in Conshohocken, PA. You will work with a team on real-world healthcare and supply chain problems, gaining hands-on experience in statistics, ML, and data engineering.

The role emphasizes learning, collaboration, and delivering analyses with guidance from senior team members. This position is based on-site with a strong mentorship component.

Qualifications

• Currently pursuing a bachelor’s degree in data science, statistics, mathematics, computer science, or related field.
• Foundational programming skills in Python and SQL.
• Understanding core statistical concepts and introductory ML techniques.
• Experience preparing and working with data, including cleaning and quality assessment.
• Familiarity with version control (Git).

Responsibilities

• Explore, clean, and prepare structured datasets for analysis and modeling.
• Build, test, and validate statistical and ML models under guidance.
• Support data pipeline development, including ETL tasks.
• Assist with model deployment, testing, and monitoring in production.
• Create documentation communicating findings to technical and business audiences.
• Collaborate with data scientists, data engineers, analysts, and stakeholders.

Skills

Python

SQL

Statistics basics

Data wrangling

Git

Education

Bachelor's degree in data science/computer science/statistics

Tools

Databricks

Azure

Job description

Cencora is seeking a Data Scientist Intern to explore data, build models, and contribute to data pipelines in Conshohocken, PA. You will work with a team on real-world healthcare and supply chain problems, gaining hands-on experience in statistics, ML, and data engineering.

The role emphasizes learning, collaboration, and delivering analyses with guidance from senior team members. This position is based on-site with a strong mentorship component.