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Garner Health is seeking a Manager of Applied Science to build and lead a team responsible for the algorithmic core of its healthcare optimization platform. The company partners with employers to redesign healthcare delivery by applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients, identifying top-performing doctors and steering members to higher-quality, lower-cost care. In five years, Garner has helped 2.5M people access better care and saved $1B in healthcare costs.
This is a hands-on management role where you will lead a team of Applied Scientists building production systems end-to-end: framing problems, defining objective functions, selecting approaches (ML, optimization, heuristics, expert systems, or hybrids), shipping solutions, and improving them against real-world outcomes. You own your team's roadmap and delivery, set technical direction while staying close to code and data, and contribute your own hands to the highest-stakes, least-defined work.
Key responsibilities include hiring and developing Applied Scientists, holding the bar on rigor and speed, defining metrics to judge solution effectiveness, turning ambiguous business goals into clear problem sets with Research, Product, Engineering, and business stakeholders, and representing your team's work to senior leadership. You will build deep understanding of the healthcare economy and Garner's role in it.
Near-term roadmap problems include: (1) Provider tiering optimization—building an algorithm that jointly optimizes geographic access and total-cost-of-care savings; (2) AI primary care doctor—fine-tuning and productionizing an LLM-based primary care experience with evaluation harnesses and quality monitoring; (3) Member engagement model—building an ML system that ingests claims data and in-app behavior to choose the right channel and moment for touchpoints (SMS, push, phone, email) to influence member behavior.
The role is based in Garner's New York City Financial District office with a requirement to work in-office three days per week (Tuesday, Wednesday, Thursday).
