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Hewlett Packard Enterprise Logo Hewlett Packard Enterprise · IT - Software Development

Data Science Intern

United States, Spring 35.00 - 46.00 USD / Hour · Job Posted August 19, 2025
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Job Description

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office. Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Responsibility

  • 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
  • May load data into the infrastructure and contributes to the creation of the hypothesis matrix
  • Prepares a portion of the data for the Exploratory Data Analysis (EDA) / hypotheses
  • Contributes to building models for the overall solution, validates results and performance
  • Contributes to the selection of the model that supports the overall solution
  • Supports the research, identification and delivery of data science solutions to problems
  • Supports visualization of the model's insights, user experience and configuration tools for the analytics model

Requirements

  • Working towards a Bachelor's and/or Master's degree with a focus in Data Science, Computer Science, Computer Engineering, Software development, or other IT related field
  • Basic knowledge of data science methodologies
  • Basic understanding of business requirements and data science objectives
  • Basic data mapping, data transfer and data migration skills
  • Basic understanding of analytics software (eg. R, SAS, SPSS, Python)
  • Basic knowledge of machine learning, data integration, and modeling skills and ETL tools (eg. Informatica, Ab Initio, Talend)
  • Basic communication and presentation skills
  • Basic data knowledge of relevant data programming languages
  • Basic knowledge of data visualization techniques

What we offer

  • Health & Wellbeing
  • Personal & Professional Development
  • Unconditional Inclusion
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