Staff Data Scientist Core Platform - Prealize Health

Prealize Health Staff Data Scientist (Core Platform )

The Role

Key Responsibilities

• Domain Expertise: Drive the end-to-end building and execution of our custom healthcare foundation models, translating high-level clinical use cases into concrete deep learning architectures and training objectives.
• Strategic Vision: Set the technical roadmap for patient risk prediction and health trajectory modeling, pioneering the use of transformer-based architectures in the healthcare domain.
• Methodological Excellence: Establish best practices for deep learning pipelines, including self-supervised pre-training, fine-tuning paradigms, and rigorous evaluation of longitudinal healthcare data.
• Technical Leadership: Own the full ML lifecycle—from data processing and research prototyping to production deployment—while mentoring junior data scientists in modern engineering practices.
• Cross-Functional Collaboration: Partner with clinicians to encode medical domain knowledge into model architectures and work with Engineering to productionize models with high reliability and low latency.
• Platform Innovation: Experiment with novel architectures and representation learning strategies to ensure our platform remains at the forefront of AI-driven healthcare insights.
• External Evangelism: Contribute to research initiatives and represent Prealize Health’s technical expertise in the broader machine learning and healthcare data science community.

Required Qualifications

• Education: PhD and/or MS in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 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.
• Deep Learning Expertise: Mastery of transformer architectures, attention mechanisms, and pre-training/fine-tuning paradigms. Hands-on experience with PyTorch or TensorFlow is mandatory.
• Programming & AI Tooling: Expert proficiency in Python and distributed computing (PySpark/Spark/SQL) for large-scale data processing.
• Proficiency in leveraging AI-assisted coding tools (e.g., Claude Code, Cursor, Codex) to accelerate development cycles and enhance code quality.
• Software Engineering Rigor: Strong skills in software design patterns, testing frameworks, CI/CD, and code quality practices.
• Strategic Mindset: Demonstrated ability to conduct independent research and translate complex findings into production systems that solve high-ambiguity problems.
• Communication: Exceptional ability to distill complex technical strategies and research findings for executive stakeholders and cross-functional teams.

Preferred Qualifications