As an intern at Roche's Global Internship Programme in Innovation & Sustainability (#IP2TIS), you have the opportunity to contribute to a project focused on making large-scale analytics workloads more sustainable by developing AI-driven insights for computing on Snowflake. Your key responsibilities include:
Extracting and analyzing compute usage data from Snowflake, including query history, warehouse usage, runtime, data scanned, and compute credits
Developing a methodology to estimate the carbon footprint of analytics workloads based on compute consumption
Identifying high-impact and inefficient queries that contribute disproportionately to compute usage
Building a prototype dashboard or application to visualize carbon impact across queries, users, teams, or workloads
Applying AI, machine learning, or LLM-based techniques to analyze SQL queries and generate optimization recommendations
Validating findings through a pilot use case on selected datasets, teams, or Snowflake environments
Documenting the methodology, assumptions, and limitations of the carbon estimation approach
Preparing a final report and presentation with key insights, optimization opportunities, and recommendations for scaling
Qualifications required for this role include:
Being enrolled or having completed your Bachelors or Masters studies at a university within the last 12 months, preferably in the field of Data Science, Data Analytics, Computer Science, Software Engineering, or Artificial Intelligence / Machine Learning
Proficiency in SQL and experience in querying and analyzing large-scale datasets
Familiarity with Snowflake or similar cloud data platforms such as BigQuery or Redshift, and ability to use R for data analysis and prototyping
Experience with data visualization tools such as Shiny dashboards; basic knowledge of AI or machine learning for pattern detection is an advantage
Strong attention to detail and ability to turn findings into practical recommendations
Strong English skills and a genuine curiosity for sustainability and AI
If you meet most but not all qualifications, Roche encourages you to apply. Please note that the internship is expected to start between 1 and 16 July 2026 and will last at least 3 months. With a mission to prevent, stop, and cure diseases, Roche aims to ensure everyone has access to healthcare for generations to come. They empower their employees to explore new possibilities, foster creativity, and deliver life-changing healthcare solutions on a global scale. As an intern at Roche's Global Internship Programme in Innovation & Sustainability (#IP2TIS), you have the opportunity to contribute to a project focused on making large-scale analytics workloads more sustainable by developing AI-driven insights for computing on Snowflake. Your key responsibilities include:
Extracting and analyzing compute usage data from Snowflake, including query history, warehouse usage, runtime, data scanned, and compute credits
Developing a methodology to estimate the carbon footprint of analytics workloads based on compute consumption
Identifying high-impact and inefficient queries that contribute disproportionately to compute usage
Building a prototype dashboard or application to visualize carbon impact across queries, users, teams, or workloads
Applying AI, machine learning, or LLM-based techniques to analyze SQL queries and generate optimization recommendations
Validating findings through a pilot use case on selected datasets, teams, or Snowflake environments
Documenting the methodology, assumptions, and limitations of the carbon estimation approach
Preparing a final report and presentation with key insights, optimization opportunities, and recommendations for scaling
Qualifications required for this role include:
Being enrolled or having completed your Bachelors or Masters studies at a university within the last 12 months, preferably in the field of Data Science, Data Analytics, Computer Science, Software Engineering, or Artificial Intelligence / Machine Learning
Proficiency in SQL and experience in querying and analyzing large-scale datasets
Familiarity with Snowflake or similar cloud data platforms such as BigQuery or Redshift, and ability to use R for data analysis and prototyping
Experience with data visualization tools such as Shiny dashboards; basic knowledge of AI or machine learning for pattern detection is an advantage
Strong attention to detail and ability to turn findings into practical recommendations
Strong English skills and a genuine curiosity for sustainability and AI
If you meet most but not all qualifications, Roche encourages you to apply. Please note that the internship is expected to start between 1 and 16 July 2026 and will last at least 3 months.
