Associate Applied Scientist

Garner Health•New York City, NY

11d•$150,000•Remote

About The Position

Garner is on a mission to transform the U.S. healthcare system by partnering with employers to redesign how healthcare works. They apply proprietary clinical metrics to a large patient dataset to identify high-performing doctors and use incentives to guide members to better care, resulting in improved health outcomes and reduced costs. The company has experienced significant growth and is looking to leverage AI to scale its impact. This role is for an individual who wants to tackle complex problems, deliver tangible results, and grow professionally within the Applied Science team. The core of the role involves developing and owning production algorithmic systems that answer critical questions for members, such as which doctor to see, expected costs, and optimal outreach strategies. This is a hands-on role focused on building and iterating on algorithms, not just analyzing data.

Requirements

A Bachelor's or Master's degree (in progress) in Computer Science, Mathematics, Statistics, Economics, or a related STEM field, with an expected graduation date of Fall 2026 or Spring 2027.
A bias toward action, quickly translating ideas into working prototypes to test approaches.
Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them.
A solid command of the methods your work calls for and the data your models depend on.
Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem.
Strong communication skills, with the ability to present your work clearly to senior stakeholders.
A desire to do work that matters: and to be held to a high standard while doing it.
You're energized by a mission with measurable outcomes, not just good intentions.
You engage with AI tools as part of how you do your best work, and hold yourself accountable to outcomes that matter beyond your team’s metrics.

Responsibilities

Ship production algorithmic systems end-to-end, from problem framing to launch to iteration
Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks
Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship
Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for
Bring new ideas to your work, experimenting with approaches beyond the obvious to get better results
Produce rigorous, well-validated work others can rely on, and review your peers' code and analyses
Build a deep understanding of the healthcare economy and Garner's place in it