Hybrid Data Science Intern: Edge-to-Cloud Analytics

Hewlett Packard Enterprise; Roseville (CA); Hybrid; USD 48,000 - 55,000; Full time

Benefits offered by this job

Health benefits

Career development

Inclusive culture

Job summary

Hewlett Packard Enterprise in the United States is seeking a Data Science Intern. The role is hybrid, requiring you to work on average 2 days per week from an HPE office in California, with exposure to data science methodologies and analytics tools.

You will contribute to data preparation, model development, and visualization, collaborating with cross‑functional teams to translate insights into actionable business outcomes.

Qualifications

• Working towards a Bachelor's and/or Master's degree in data science, computer science, computer engineering, software development, or IT-related field.
• Basic knowledge of data science methodologies.
• Basic data mapping, data transfer and data migration skills; familiarity with analytics software (R, SAS, SPSS, Python).
• Basic knowledge of machine learning, data integration, modeling skills and ETL tools.

Responsibilities

• Participates in the analysis and validation of data sets/solutions/user experience.
• Aids in the development, enhancement and maintenance of a client’s metadata based on analytic objectives.
• Contributes to building models for the overall solution and validates results and performance.
• Supports the research, identification and delivery of data science solutions to problems.
• Supports visualization of the model’s insights, user experience and configuration tools.

Skills

Data science basics

Python

R

SAS

SPSS

ETL tools

Python data visualization

Education

Bachelor's or Master's in DS/CS/Software

Tools

Informatica

Ab Initio

Talend

Job description

Hewlett Packard Enterprise in the United States is seeking a Data Science Intern. The role is hybrid, requiring you to work on average 2 days per week from an HPE office in California, with exposure to data science methodologies and analytics tools.

You will contribute to data preparation, model development, and visualization, collaborating with cross‑functional teams to translate insights into actionable business outcomes.