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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

20Open Positions

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Intern - Data Science - Global IT (m/f/x)

Hilti Austria
Found 1 month ago
Location
Buchs, Switzerland
Duration (Months)
6 Months
Time
Not disclosed
Work Mode
Not disclosed
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Bachelor
  • Master

Skills & Qualifications

Technical Skills

  • Python
  • SQL
  • Azure
  • AWS
  • CI/CD

Soft Skills

  • communication
  • presentation skills
  • strategic mindset
  • problem-solving approach
  • curiosity
  • willingness to learn quickly

Job Description

As a Data Science Intern, you’ll work at the intersection of advanced analytics and real-world business needs. You will participate in discovery phases to understand business requirements, identify data-driven opportunities, and translate them into actionable use cases. Your daily work involves designing experiments, testing hypotheses, and developing statistical or machine learning models using Python. You’ll be embedded in an experienced team of data engineers and data scientists, benefitting from pair programming, version control, and a fully established CI/CD environment. You’ll work with diverse data sources-internal, external, structured, and unstructured-and assess what is relevant for each use case. You will help shape strategies for data collection, integration, and retention, and will collaborate closely with domain experts across the company. A key part of the role is communicating complex insights into clear, business-friendly language. You’ll support stakeholders in adopting data science methods, run statistical validations, and guide teams through agile delivery using Scrum. Throughout your internship, you’ll contribute to impactful, production-oriented solutions that enable better decisions across Hilti’s digital business.

Requirements

  • Bachelor’s or Master’s studies in Data Science, Computer Science, Engineering, Mathematics, Physics, Statistics, or similar.
  • Hands-on experience with Python and SQL; familiarity with cloud platforms (Azure or AWS).
  • Basic knowledge of software engineering practices (architecture basics, version control, CI/CD).
  • Strong communication and presentation skills, with the ability to explain complex analytics to non-experts.
  • A strategic mindset and problem-solving approach, with curiosity and willingness to learn quickly.

Related Field

  • Data & Analytics

Related Subfield

  • Data Science
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