Causalis is a VC-backed startup partnering with the world’s leading pharma companies, building
machine learning solutions to bring causal intelligence to healthcare. We are developing a platform of
solutions based on novel and proprietary causal AI techniques, to help doctors, patients, and
researchers understand and act on the cause-effect relationships in medical data. We are a
multi-disciplinary, international team of experts in AI and ML, causal inference and data science,
healthcare and medicine. We are looking for smart, driven and overall extraordinary individuals who
are passionate about changing the world of personalized medicine, and eager to shape the future of
Please contact us with CV/resume at
Data Science
We're looking for an experienced data scientist to join as one of the first members of the data science
team, with the skills to take ownership from idea through implementation and deployment. You will be
engaged in the early data exploration phase, health data engineering, development of causal models
and other ML methods, evaluation techniques, and eventually product integration and follow-ups -- the
essential challenges to make Causalis deliver ML solutions.
How you’ll contribute:
Apply state-of-the-art methods in health research to improve and validate our ML and data
science capabilities
Define, design, and execute data engineering and ML tasks with a high bar for quality and
Collaborate with infrastructure engineers to design and implement data pipelines end-to-end
with complex data types to fuel ML experiments
Work with internal and external domain experts to define and execute the needed solutions in
Our ideal candidate will bring:
4+ years of experience working as a data scientist
Strong experience with ML and data science in research and production environments (ideally
with causal inference methods)
Strong Python skills
Excellent communication skills and ability to work with technical and non-technical partners
from many teams
Nice to have:
Experience working in the healthcare industry
Deep knowledge of data-driven research in healthcare
MS/PhD in a relevant engineering or science field
Experience with ML explainability methods
Strong experience with NLP
Experience with imaging data
Experience with genetic data