Junior data scientist/Statistician

At Cosmo, we are at the forefront of revolutionizing healthcare through our groundbreaking technology. With our innovative advancements in live endoscopy, we are transforming the landscape of medical diagnostics. We leverage AI to empower physicians, enabling them to make well-informed decisions and significantly improve the lives of their patients. Our dedication to excellence has resulted in creating GI Genius: our AI-enabled medical device for live endoscopy has received FDA approval and is successfully deployed in hospitals worldwide, making a significant impact in the field of healthcare. Check out our website for more information at

We are looking for a Junior Data Scientist with strong statistical foundations. You will work at the intersection of clinical research, AI validation, and regulatory-grade evidence generation.

This is a hands-on, scientifically driven position. You will design experiments, build statistical models, analyze clinical and perceptual data, and contribute to publications in top-tier journals. The role spans multiple active programs, including psychophysical studies of treatment perception, AI-assisted diagnostic performance trials, and secondary analyses of clinical data.

If you are early in your career but intellectually ambitious, this role offers an uncommon opportunity: a front-row seat to how AI is changing healthcare from the inside.

Key Responsibilities

• Design and execute statistical analysis plans for clinical and perceptual studies, including pre-registration, power analysis, and sample size justification.
• Develop and apply hierarchical Bayesian models, mixed-effects models, and adaptive experimental designs.
• Perform secondary analyses on Phase 2/3 clinical trial datasets.
• Collaborate in multi-reader multi-case (MRMC) analyses and signal detection theory assessments for AI-assisted diagnostic studies.
• Collaborate with academic co-investigators and contribute to manuscripts targeting high-impact peer-reviewed journals.
• Build reproducible analytical pipelines with clear documentation and version control.
• Support regulatory and Health Technology Assessment submissions with robust statistical evidence.

REQUIREMENTS

Education

• Master’s degree or PhD in Statistics, Biostatistics, Applied Mathematics, or a quantitative discipline with strong statistical training.
• Solid grounding in frequentist and Bayesian inference, experimental design, and hypothesis testing.
• Proficiency in Python and/or R for data analysis and statistical modeling.
• Ability to design experiments and justify sample sizes from first principles.
• Strong written and verbal communication skills, including the ability to explain statistical concepts to non-technical stakeholders.
• Comfort working in English as the primary working language for scientific output.

Experience

• Experience with clinical trial methodology, survival analysis, or longitudinal data analysis.
• Familiarity with Bayesian hierarchical models (e.g., Stan, PyMC, brms).
• Exposure to psychophysics, signal detection theory, or perceptual measurement.
• Track record of independent research: preprints, open-source contributions, replication studies, or published work.
• Interest in regulated environments (FDA, EMA) where evidentiary standards matter more than benchmark leaderboard positions.
• Familiarity with modern ML tooling (PyTorch, JAX) as a complement to statistical thinking.

Physical Requirements:

Expected travel is 30%

Equal Opportunity Statement:

We support equal opportunities, without any discrimination; The research complies with Legislative Decree 198/2006