Staff Applied Scientist

Garner is on a mission to transform the U.S. healthcare system and were 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.

The result is a rare win win better care and lower costs for both members and 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 youve ever wanted your work to solve a problem that touches every person in this country this is the opportunity to do exactly that. Youd 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.

We are seeking an exceptional Staff Applied Researcher to join our Applied Science team. You will be responsible for building the algorithmic systems that power Garner determining how we evaluate providers make recommendations and optimize for outcomes across cost quality and access.

You will be responsible for turning ambiguous real-world problems into systems that deliver measurable impact defining the objective functions metrics and logic that drive our product. You will own these systems end-to-end from problem definition through production and ongoing performance.

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.

• Own the most ambiguous high-stakes problems facing the company end-to-end and set how the team frames and approaches them
• 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 and set the standard for how the team selects and applies these approaches
• Deliver algorithmic breakthroughs that move the companys most important metrics pioneering approaches that become how applied science is done at Garner
• Review applied science work at the highest level across the company ensuring the methods used across teams are sound and correctly applied
• Build a deep understanding of the healthcare economy and Garners place in it

To make the role concrete here are three problems on our near-term roadmap:

• Provider tiering optimization. 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.
• AI primary care doctor. 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.
• Member engagement model. 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.

• 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
• 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
• Recognized technical authority with the judgment to ensure the techniques used across an organization are sound
• Strong judgment in choosing between statistical models heuristics optimization approaches and simpler algorithmic methods depending on the problem
• Strong communication skills including at the executive level with a track record of driving alignment across an organization
• A desire to be a part of a high-performing mission-driven team that operates with urgency a strong sense of individual accountability and a commitment to authentic feedback

Youll work on problems that matter at a company working to change healthcare at scale. Youll work at the intersection of AI and systemic healthcare reform where the problems we solve are as interesting and compelling as the mission.

At Garner youll take on real ambitious problems with real ownership and autonomy alongside exceptional principles-based people who genuinely want you to win. Its demanding by design. Youll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isnt the right fit for everyone and thats intentional. The people here are driven by whats at stake for real people and thats what gives our intensity its purpose.

• Python SQL AWS Snowflake pandas XGBoost PyTorch HuggingFace modern LLM tooling and eval frameworks. We pick tools based on the problem not the resume bring your judgment.

This is a unique opportunity to work on high-impact search problems in healthcare helping shape how members find better care through algorithmic systems that directly influence healthcare outcomes.

The target base comp range for this position is $260000 $382000. Individual compensation for this role will depend on various factors including qualifications skills and applicable addition to base compensation this role is eligible to participate in our equity incentive and competitive benefits plans including but not limited to: flexible PTO Medical/Dental/Vision plan options 401(k) with company match flexible spending accounts Teladoc Health and more.