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Data Science Intern

Job in Spring, Harris County, Texas, 77391, USA
Listing for: Hewlett-Packard Company
Apprenticeship/Internship position
Listed on 2026-06-26
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Data Science Manager, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 70000 - 90000 USD Yearly USD 70000.00 90000.00 YEAR
Job Description & How to Apply Below

Innovation is in HP’s DNA. From our origins in a Palo Alto garage in 1939, to our current position as one of the world’s leading technology companies, HP has grown to become a leader in technology and corporate culture, inspiring innovators, and entrepreneurs around the globe. HP brings together a portfolio that spans printing, personal computing, software, and services to serve more than 1 billion customers in over 170 countries.

We are committed to fostering a diverse and inclusive workplace that attracts exceptional talent and to supporting our employees to succeed at all levels. We dream in over 35 languages and share one mission: to engineer experiences that amaze.

Responsibilities
  • Perform exploratory data analysis on new datasets to generate insights and hypotheses that can help drive business value
  • Learn about existing data science models at HP, and research ways to potentially improve them
  • Identify and evaluate potential methodologies to tackle existing business problems at HP
  • Explore new technologies and generate a proof of concept on how it can be deployed at HP
Qualifications

Master's degree 1st year

About HP

You’re out to reimagine and reinvent what’s possible—in your career as well as the world around you. So are we. We love taking on tough challenges, disrupting the status quo, and creating what’s next. We’re in search of talented people who are inspired by big challenges, driven to learn and grow, and dedicated to making a meaningful difference.

HP is a technology company that operates in more than 170 countries around the world united in creating technology that makes life better for everyone, everywhere.

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