Staff Data Scientist (SME: Healthcare Financial Risk & Underwriting)

Staff Data Scientist (SME: Healthcare Financial Risk & Underwriting)

About Prealize Health
Prealize Health is a predictive analytics company that leverages machine learning and clinical expertise to help patients obtain better care, sooner. Most healthcare today is reactive – care is delivered when someone is already ill. We believe healthcare should be about keeping individuals and their families well to prevent them from ever becoming sick.

Building on years of published research from our founders at Stanford University, our mission is to provide patients, providers, and payers with the insights they need to improve health outcomes and prevent adverse medical events. We are committed to helping healthcare organizations "see around the corner" to take a proactive approach to wellness.

The Role
As a Staff Data Scientist and the primary SME for Healthcare Financial Risk & Underwriting , you will serve as the technical authority for our most critical Healthcare financial risk and underwriting modeling domains. You will bridge the gap between complex actuarial needs and cutting-edge machine learning, defining the technical roadmap to scale predictive models for risk adjustment and underwriting.

This is a strategic, high-impact role where you will lead the evolution of our predictive models, shaping how we evaluate and power the next generation of our underwriting product.

Key Responsibilities

• Domain Expertise: Act as the Subject Matter Expert (SME), drive the end-to-end building and execution of our Risk & Underwriting AI models, directly translating actuarial and healthcare financial risk expertise into high-performance AI models and rigorous evaluation frameworks.
• Strategic Vision: Set the technical roadmap and lead the development of ML models focused on healthcare financial risk stratification and financial underwriting.
• Methodological Excellence: Establish best practices for model building, model validation, and rigorous back testing/benchmarking across the data science organization to drive high performance models, while maintaining stability and alignment of models.
• Technical Leadership: Mentor junior data scientists, fostering a culture of rigorous research, high-quality engineering, and innovation.
• Cross-Functional Collaboration: Partner with clinicians to translate medical knowledge into data-driven hypotheses and with Product/Executive teams to align technical capabilities with market opportunities.
• Platform Innovation: Work with Engineering to design the next generation of our platform’s quality and extensibility, ensuring it remains performant for millions of patients.
• External Evangelism: Represent Prealize Health’s technical expertise to external strategic partners and stay at the forefront of literature in ML, Actuarial Science, and Biostatistics.

Required Qualifications

• Education: PhD and/or MS in Statistics, Biostatistics, Economics, Computer Science, or a related quantitative field.
• Experience: 8–10+ years of experience building and deploying commercial-grade data science products with a proven track record of technical leadership.
• Domain Expertise: Deep experience building and validating models for healthcare underwriting use cases. Mastery of industry-standard risk scores and large-scale claims data is mandatory.
• Programming & AI Tooling: Expert proficiency in Python and distributed computing ( PySpark/Spark/SQL ).
• Proficiency in leveraging AI-assisted coding tools (e.g., Claude Code, Cursor, Codex) to accelerate development cycles and enhance code quality.
• Statistical Rigor: Expert-level understanding of model evaluation metrics (e.g., Gini, lift, calibration), back testing frameworks, and validation protocols for high-stakes predictive modeling.
• Strategic Mindset: Demonstrated ability to lead cross-functional projects, influence technical roadmaps, and solve high-ambiguity problems in high-dimensional datasets.
• Communication: Exceptional ability to distill complex technical strategies for executive stakeholders and external partners.

Preferred Skills

• Deep Learning Expertise: Mastery of transformer architectures, attention mechanisms, and pre-training/fine-tuning paradigms. Hands-on experience with PyTorch or TensorFlow is preferred.

We Offer:

• Flexible work environment
• Competitive base salary plus a generous bonus and equity plan
• Paid time off including holidays
• Medical, dental, vision
• 401k
• Wellness and home office benefits, and more

Pay Transparency:
The target salary range is $180,000 to $220,000 annually. Base pay offered may vary within the posted range based on several factors, including but not limited to education, job-related knowledge, skills, experience, and location.

Diversity, Equity & Inclusion:
Prealize embraces diversity and equal opportunity in a serious way. We are committed to building a team that unites a variety of backgrounds, perspectives, and skills. The more inclusive we are, the greater our impact will be.