Data Scientist (San Francisco)

We're working with a Series A health tech start-up pioneering a revolutionary approach to healthcare AI, developing neurosymbolic systems that combine statistical learning with structured medical knowledge. Their technology is being adopted by leading health systems and insurers to enhance patient outcomes through advanced predictive analytics.

We're seeking Machine Learning Engineers who excel at the intersection of data science, modeling, and software engineering. You'll design and implement models that extract insights from longitudinal healthcare data, balancing analytical rigor, interpretability, and scalability.

This role offers a unique opportunity to tackle foundational modeling challenges in healthcare, where your contributions will directly influence clinical, actuarial, and policy decisions.

Key Responsibilities

• Develop predictive models to forecast disease progression, healthcare utilization, and costs using temporal clinical data (claims, EHR, laboratory results, pharmacy records)
• Design interpretable and explainable ML solutions that earn the trust of clinicians, actuaries, and healthcare decision-makers
• Research and prototype innovative approaches leveraging both classical and modern machine learning techniques
• Build robust, scalable ML pipelines for training, validation, and deployment in distributed computing environments
• Collaborate cross-functionally with data engineers, clinicians, and product teams to ensure models address real-world healthcare needs
• Communicate findings and methodologies effectively through visualizations, documentation, and technical presentations

Required Qualifications

Bonus Qualifications