Data Scientist

MedINT · telaviv

Medint is a Tel Aviv-based health-tech company building the first human-in-the-loop clinical decision support platform for complex, multidisciplinary patient cases. Our AI system helps physicians managing complicated cases surface verified, patient-specific evidence they can inspect, question, and act on. We don't replace clinical judgment; we make sure it's never limited by incomplete evidence. Medint is on a mission to ensure that no patient's treatment is held back when the guidelines are not enough. What's it like to work at Medint? We're a fast-moving team building at the intersection of medicine and AI, where clinical rigor and technical execution sit side by side. We move quickly, hold our work to a high bar of clinical accuracy, and want people who are motivated by seeing their expertise directly translate into a product used in real clinical decisions. As we grow Medint's AI product capabilities, we're looking for a Data Scientist to join our R&D team and help us push the boundaries of what our clinical AI system can do. Responsibilities Design, develop, and evaluate core AI/ML components that power Medint's evidence-retrieval and clinical decision support capabilities. Work closely with clinicians, engineers, and product to translate open-ended clinical problems into well-scoped data science problems. Analyze large, messy, real-world clinical and biomedical datasets to uncover patterns that inform product direction and model design. Partner with engineering to integrate models and data-driven features into the product, contributing directly to the implementation and maintenance of production code. Continuously research and apply state-of-the-art techniques in GenAI, machine learning, and LLMs to healthcare-specific challenges. Communicate findings and trade-offs clearly to both technical and non-technical stakeholders, including clinical staff. Requirements 4+ years of experience as a Data Scientist, working on real-world, production-facing problems. A BSc or higher in a STEM field, or equivalent professional experience. Strong proficiency in Python and standard data science / ML libraries. Solid foundation in statistics, machine learning, and experimental design. Experience working with large-scale, unstructured, or noisy datasets. Recent hands-on experience with GenAI, LLMs, RAG, and the relevant tools and evaluation methods. Multi-agent and agent harness architectures are a plus. Strong analytical thinking and the ability to independently scope and drive a project from question to production. Excellent communication skills and comfort working cross-functionally with clinicians, engineers, and product owners. A genuine interest in healthcare and a strong sense of responsibility given the clinical stakes of our work. Advantages Familiarity with MLOps practices and tooling (e.g. model versioning, monitoring, CI/CD for ML pipelines). Experience working with clinical, biomedical, or other regulated/high-stakes data. Background or coursework in a life sciences, biomedical, or clinical field. Hands-on NLP experience. Understanding of Transformers, fine-tuning, and evaluation methods, ideally with recent hands-on experience. Familiarity with information retrieval algorithms and evaluation approaches.

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