Job Description

What a College Intern - Data Science does at HP:

You will be attached to the "Manufacturing Intelligence Team". Work with an enterprising team of data scientists and build solutions to track, analyze and visualize the manufacturing and outbound quality of our supplies. Generate deep insights through the analysis of data and understanding of operational processes and turn them into actionable recommendations. Develop methodologies for optimizing our business processes through data visualization, real-time monitoring, predictive analytics etc. Develop scalable end to end data science solutions.

Individuals who do well in this role at HP, usually possess:

Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Business Analytics, Information Systems, Statistics with good experience in programming. Students graduating in 2026 or 2027 will be prioritized. Able to commit for a 5-6 months full time internship, starting in January 2026. Excellent analytical thinking, programming (using Python is desirable), and problem-solving skills. Knowledge of data analytics, machine learning, data warehousing, database management (preferably using SQL), data visualization, web applications and application programming interfaces (APIs). Fundamental knowledge of statistics and probability. Software engineering fundamentals (clean code, code readability, code documentation, etc). Previous experience with microservices and container management services such as Docker. Good visualization skills to create real-time dashboards and/or reports to inform trends and insights. Ability to communicate ideas clearly and coherently in a convincing manner.
Sustainable impact is HP's commitment to create positive, lasting change for the planet, its people, and our communities. This serves as a guiding principle for delivering on our corporate vision - to create technology that makes life better for everyone, everywhere.

HP is a Human Capital Partner - we commit to human capital development and adopting progressive workplace practices in Singapore.

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