Senior Data Scientist

Barcelona, on-site

Causal Foundry is looking for an experienced, Senior Data Scientist with PhD to join our team in Barcelona. Your role will be to deeply analyse partner data, identifying and designing effective solutions, analyzing their impact, while maintaining seamless collaboration with other teams at CF such as Engineering and Partnerships. This role demands a keen focus on both the technical and impact aspects of data science, driving excellence in our product delivery and partnership management.

The company

Causal Foundry (CF) builds AI products to solve operational challenges across diverse use cases including global health, supply chain, industry and education. CF’s AI Platform, Kenkai, allows existing digital applications to use advanced personalization technology typically reserved for prominent industry actors. The platform ingests data from digital tools through domain-specific SDK and implements algorithms for predictions and adaptive interventions. The latter uses various models of linear and contextual bandits, restless bandits for resource allocation, and networked restless bandits for budgeted interventions in communities. CF continuously evolves its platform to deliver the latest AI methods to provide comprehensive services to its partners.

Role responsibilities

• Take ownership of the Rwanda data science workstream, helping drive analytical, product and operational decisions with RSSB, RMS, RBC, MOH or other related stakeholders.
• Work with CF leadership and partner teams to identify the most important operational questions and translate them into clear analytical, causal, predictive or decision-support problems.
• Turn ambiguous product, health and operational questions into clear analytical, causal or predictive problems.
• Build and validate models for forecasting, risk stratification, personalisation, resource allocation and decision support.
• Design experiments and causal analyses that tell us not only what happened, but what genuinely worked, for whom and why.
• Make sense of complex, imperfect and longitudinal data without losing sight of bias, uncertainty, ethics or operational reality.
• Work shoulder-to-shoulder with ML engineers, data engineers, product specialists and domain experts to move strong ideas into production.
• Tell a compelling, precise story with data, whether the audience is a technical peer, a product team or a public-sector decision-maker, raising the bar through mentorship and thoughtful technical leadership.
• Collaborate with partners (and with the end users of their technology whenever possible) to gain a deep understanding of their business and needs, summarize & communicate internal analyses to partners (travel required).
• Become an active user of Causal Foundry’s Platform and other CF technologies, and provide feedback to the Engineering team as necessary on functionalities, data quality and completeness, and overall user experience.
• Support the development of externally facing materials such as scientific papers, marketing materials, and grant applications, providing the necessary technical expertise (writing and reviewing the technical components).

Required experience

• PhD in statistics, physics, computer science, mathematics, economics, or a closely related quantitative field.
• Substantial post-PhD experience using data science to influence real decisions—not only publishing research or building prototypes.
• Hands-on experience with agentic workflows and AI coding tools such as Claude Code, Codex, or Cursor, using them effectively for analysis, prototyping, and development.
• Deeply fluent in statistical modelling, machine learning, experimental design and causal inference, and you know how to evaluate models honestly.
• Able to write advanced Python and SQL and care about reproducibility, testing, version control and code that other people can trust.
• Comfortable with messy, high-stakes data and can balance methodological rigour with the need to deliver.
• Communicate complex trade-offs simply, collaborate generously and take ownership without waiting to be told what to do.

And...

• We would be especially excited if you bring experience in: global health, healthcare delivery, low- and middle-income country settings, supply chains or mission-critical social systems.
• Expertise in reinforcement learning or contextual bandits, time-series forecasting, survival analysis, Bayesian methods, optimization, recommender systems, NLP, and deep learning will also be highly valuable.
• A strong publication or open-source record, experience deploying models at scale or evidence that you have helped other scientists grow will strengthen your application.

Why Causal Foundry

• Your work will target real inequalities real operational decisions and improve outcomes
• Explore advanced methods, then see them tested, deployed and measured in the world.
• Work with ambitious people from diverse backgrounds, across disciplines, move quickly and take meaningful responsibility.
• Collaborate across cultures and geographies on problems that rarely have easy answers.