Associate Applied Scientist

About the role

Garner is on a mission to transform the U.S. healthcare system by partnering with employers to redesign how healthcare works. Using 550+ proprietary clinical metrics across 80+ specialties and a dataset of 320M+ patients, Garner identifies the best‑performing doctors and steers members to higher‑quality, lower‑cost care. In five years the company has helped over 2.5 million people access better care and saved $1 billion in healthcare costs. As an Associate Applied Scientist you will join the Applied Science team, owning production algorithmic systems end‑to‑end and applying AI to scale impact in healthcare.

Responsibilities

• Ship production algorithmic systems end‑to‑end: problem framing, objective definition, approach selection, implementation, and iteration.
• Frame messy, real‑world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks.
• Define the metrics needed to judge solution validity and validate before shipping.
• Choose the right approach for each problem — machine learning, optimization, heuristics, expert systems, or hybrids — based on what the problem calls for.
• Bring new ideas, experimenting beyond obvious solutions to improve results.
• Produce rigorous, well‑validated work that peers can rely on; review peers’ code and analyses.
• Build a deep understanding of the healthcare economy and Garner’s role within it.
• Near‑term projects include:
• Provider tiering optimization: jointly optimize geographic access and total‑cost‑of‑care savings across the doctor network.
• Member engagement model: ML system that ingests claims and in‑app behavior to select the optimal channel and timing (SMS, push, phone, email) for influencing member behavior toward better‑quality, lower‑cost care.

Requirements

• Bias toward action: quickly translate ideas into working prototypes to test approaches.
• Strong applied problem‑solving skills, with ability to define good metrics and deliver solutions that improve them.
• 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, and simpler algorithmic methods depending on the problem.
• Strong communication skills, able to present work clearly to senior stakeholders.
• Desire to do work that matters and to be held to a high standard while doing it.
• Energized by a mission with measurable outcomes, not just good intentions.
• Engage with AI tools as part of doing your best work and hold yourself accountable to outcomes that matter beyond your team’s metrics.

Qualifications

• Bachelor’s or Master’s degree (in progress) in Computer Science, Mathematics, Statistics, Economics, or a related STEM field.
• Expected graduation date: Fall 2026 or Spring 2027.

Skills

• Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and evaluation frameworks.

Benefits

• Flexible PTO
• Medical/Dental/Vision plan options
• 401(k) with company match
• Flexible spending accounts
• Teladoc Health
• Equity incentive plan

Pay

The target base compensation range for this role is $150,000. Individual compensation will depend on qualifications, skills, and applicable laws. In addition to base pay, the role is eligible to participate in the company’s equity incentive plan.