Staff Data Scientist (Core Platform)

Join Prealize Health as a Staff Data Scientist, where you will lead the development of next-generation patient trajectory and risk prediction systems. You will bridge the gap between state-of-the-art research in self-supervised learning and real-world healthcare applications. This strategic role will shape how we process millions of claims, lab results, and EHR records to influence the health trajectory of millions of patients. You will establish best practices for deep learning pipelines, own the full ML lifecycle, and collaborate with clinicians and engineering teams. Additionally, you will contribute to research initiatives and represent Prealize Health's technical expertise in the broader machine learning and healthcare data science community.

• Conduire le développement de systèmes de prédiction des trajectoires des patients et des risques, en mettant l'accent sur les modèles de fondation.
• Établir la feuille de route technique pour la prédiction des risques des patients et la modélisation des trajectoires de santé, en pionnier l'utilisation des architectures basées sur les transformateurs.
• Posséder l'ensemble du cycle de vie de l'apprentissage automatique, de la préparation des données à la production, tout en mentorant les scientifiques des données juniors.
• Proficiency in leveraging AI-assisted coding tools (e.g., Claude Code, Cursor, Codex) to accelerate development cycles and enhance code quality
• Strategic Mindset: Demonstrated ability to conduct independent research and translate complex findings into production systems that solve high-ambiguity problems
• Software Engineering Rigor: Strong skills in software design patterns, testing frameworks, CI/CD, and code quality practices
• Deep Learning Expertise: Mastery of transformer architectures, attention mechanisms, and pre-training/fine-tuning paradigms. Hands-on experience with PyTorch or TensorFlow is mandatory
• Experience: 6–8+ years of experience (with 4+ years specifically building and deploying ML systems in production) with a proven track record of technical leadership
• Programming & AI Tooling: Expert proficiency in Python and distributed computing (PySpark/Spark/SQL) for large-scale data processing
• Education: PhD and/or MS in Computer Science, Machine Learning, Statistics, or a related quantitative field
• Communication: Exceptional ability to distill complex technical strategies and research findings for executive stakeholders and cross-functional teams
• Healthcare Domain: Experience with large-scale structured healthcare data (Claims, ICD/CPT codes, EHR systems like Epic/Cerner)
• Advanced MLOps: Experience with MLOps tooling such as MLflow, Weights & Biases, and cloud platforms (AWS preferred)
• Specialized Modeling: Familiarity with causal inference, longitudinal modeling, or self-supervised representation learning