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46103Open Positions

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Internship in Innovation & Sustainability

Roche
Found 1 week ago
Location
Basel, Switzerland
Time
Full-time
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 week ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • sustainability topics
  • data science
  • AI
  • data engineering
  • data aggregation
  • exploratory data analysis
  • predictive modeling
  • validation

Soft Skills

  • stakeholder management
  • cross-functional communication

Job Description

Our Global Internship Programme in Innovation & Sustainability (#IP2TIS) offers a unique opportunity for passionate individuals to gain hands-on experience in the pharmaceutical industry while making a positive impact on the world. Are you ready to join a global network spanning 20+ countries, where bright minds collaborate to tackle real-world challenges in Innovation & Sustainability? Do you want to work on impactful projects, shape the future, and drive change from within? As an intern, you will contribute to a project focused on using AI-driven analytics to accelerate site-level Ecobalance and decarbonization decisions. The project aims to transform raw energy consumption and CO2 emissions data into proactive insights that help site managers and sustainability teams take faster, more informed action. Within your first 3 months, you are expected to help develop a predictive trend analysis model, support anomaly detection logic, create a library of AI-generated prompts, and contribute to a digital prototype that simulates the impact of different sustainability measures. Your work will help reduce the time between data collection and environmental action, strengthen data-driven decision-making, and support Roche’s broader net-zero ambitions. This internship offers a unique opportunity to build AI tools that turn sustainability data into practical environmental action.

Requirements

  • Knowledgeable in sustainability topics, data science, AI, and data engineering
  • Comfortable working with data aggregation, exploratory data analysis, predictive modeling, and validation
  • Able to translate technical findings into clear and practical insights for non-technical stakeholders
  • Strong in stakeholder management and cross-functional communication
  • Fluent in English

Related Field

  • Data & Analytics

Related Subfield

  • Data Science

Languages

  • English
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