<div class="content-intro"><h2><strong>What you’ll be part of</strong></h2> <p>Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster.</p> <p>The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can.</p></div><h2><strong>About the role:</strong></h2> <p>We are seeking an exceptional Manager, Product Applied Science to build and lead a team at the core of Garner's product. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them.</p> <p>This is a hands-on management role. You are responsible for the overall technical direction of your squad, building alongside your team of Applied Scientists to solve some of the hardest problems at the company.</p> <p>This is not a dashboards or descriptive-analytics team. Your team owns production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is leading a research pod at a top hedge fund.</p> <h2><strong>Where you will work:</strong></h2> <p>This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday.</p> <h2><strong>What you will do:</strong></h2> <ul> <li>Lead a team of 4-6 — hire, coach, and develop them, hold the bar on both rigor and speed, and help raise that bar across Applied Science</li> <li>Own the Population Health team and their outputs as a core responsibility </li> <li>Own your team's roadmap and delivery: what gets built, in what order, and whether it ships</li> <li>Set technical direction, and get in the weeds to do it — stay close enough to the code and the data to call the approach yourself, whether that's machine learning, optimization, a heuristic, or a simple rule, and set the standard for how your team makes that call</li> <li>Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship</li> <li>Put your own hands on the problems where your judgment matters most — the highest-stakes, least-defined work — and deliver the algorithmic step-changes that move metrics like total-cost-of-care savings, steerage, and member engagement</li> <li>Turn ambiguous business goals into a clear problem set alongside Research, Product, Engineering, and business stakeholders, and represent your team's work to senior leadership</li> <li>Set the quality bar: review your team's work with rigor, and define the metrics that decide whether a solution is working</li> <li>Build a deep understanding of the healthcare economy and Garner's place in it</li> <li> </li> </ul> <p>To make the role concrete, here are three problems on our near-term roadmap:</p> <ul> <li><strong>Provider tiering optimization. </strong>Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions.</li> <li><strong>AI primary care doctor. </strong>Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely.</li> <li><strong>Member engagement model. </strong>Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care.</li> </ul> <h2><strong>The ideal candidate has:</strong></h2> <ul> <li>6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant advanced degree, PhDs preferred</li> <li>Deep technical credibility, with the range and judgment to lead scientists who are experts in their own right, and the willingness to stay hands-on</li> <li>Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem</li> <li>Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them</li> <li>A bias toward action, quickly translating ideas into working prototypes to test approaches</li> <li>Strong communicat