Barcelona, on-site - 20 hours per week

Causal Foundry is looking for a curious and motivated Statistics Intern to join our Data Science team in Barcelona. You will help analyse complex datasets, evaluate the impact of AI-driven interventions and turn real-world questions into clear statistical analyses.
Working alongside data scientists, engineers, product specialists and domain experts, you will gain practical experience applying statistical methods to operational challenges in areas such as general health, supply chains, industry and education.
We welcome applications from Students enrolled in Universities in the Barcelona area.

The company

Causal Foundry (CF) builds AI products to solve operational challenges across diverse use cases, including global health, supply chains, industry and education.
CF’s AI platform, Kenkai, enables existing digital applications to use advanced personalization technology typically reserved for prominent industry actors.



The platform ingests data from digital tools through domain-specific SDKs and applies algorithms for prediction and adaptive intervention. CF continuously evolves its platform to deliver advanced AI methods and comprehensive services to its partners.

As a Statistics Intern, you will:

Conduct descriptive and exploratory analyses to identify patterns, trends and data-quality issues.
Apply appropriate statistical methods to answer product, health and operational questions.
Help design and evaluate experiments, including defining metrics, analyzing results and communicating uncertainty.
Support causal, predictive and time-to-event analyses under the guidance of senior members of the Data Science team.
Build reproducible analyses using Python, SQL or R, with clear documentation and version control.
Create concise reports, visualizations and presentations for technical and non-technical audiences.

What we are looking for

Currently completing a bachelor’s or master’s degree in statistics or mathematics.
A sound found

📌 Statistics Intern (Barcelona)
🏢 Causal Foundry
📍 Barcelona