Applied Scientist III

Garnerhealth
New York, NY
On-site

Who this role is best for

Best suited to candidates with strong technical and healthcare domain expertise working in a high-stakes, mission-driven environment.

Best fit for

  • Candidates with experience in building and deploying AI systems in healthcare settings
    — “You will design, develop, and deploy the algorithmic systems that power Garner's products
  • Individuals who have a background in solving high-stakes, ambiguous problems with measurable impact
    — “Own the most ambiguous, high-stakes problems on the team end-to-end
  • Candidates who have a track record of defining metrics and delivering solutions that improve them
    — “Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them

Things to consider

  • Significant responsibility for validating and proving out novel algorithmic approaches
    — “Find novel ways to frame and solve the team's hardest problems, proving out approaches that others build on
  • Requires fluency in a broad technical stack, including LLMs and optimization frameworks
    — “Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks

How to stand out

  • Highlight experience with real-world deployment and impact measurement of algorithmic systems
    — “The quality of those answers is determined by the algorithms behind them
  • Showcase a habit of staying current with AI advancements and applying them strategically
    — “Deep technical range, with fluency across Garner's data and a habit of staying current with advances in the field
  • Emphasize experience in translating complex ideas into clear decision frameworks for stakeholders
    — “The ability to synthesize complex algorithmic ideas for senior and external stakeholders
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · CompanyLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designing and deploying algorithmic systems
  • optimizing healthcare solutions
  • validating solutions
Typical background
AI researchhealthcare analyticsmachine learning

Skills & requirements

Required

Machine LearningAlgorithm DesignOptimizationHealthcare AnalyticsAI Systems

Preferred

Healthcare EconomicsProvider Tiering

Stack & domain

AIMachine LearningOptimizationLeadershipCommunicationHealthcare

About the role

Original posting from Garnerhealth via Greenhouse

What you’ll be part of

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.

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.

About the Role:

We are seeking an exceptional Senior Applied Scientist to join our Applied Science team. In this role, you will design, develop, and deploy the algorithmic systems that power Garner's products and drive meaningful impact for our members. 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.

This is not a dashboards or descriptive-analytics role. You will own 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 a quantitative researcher at a top hedge fund.

What you will do:

Own the most ambiguous, high-stakes problems on the team end-to-end, and serve as a technical resource others rely on

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

Find novel ways to frame and solve the team's hardest problems, proving out approaches that others build on

Set the bar for quality by reviewing others' work with rigor, and build the standards and evaluation tooling the team relies on

Build a deep understanding of the healthcare economy and Garner's 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.

The ideal candidate has:

4+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 2+ 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

Deep technical range, with fluency across Garner's data and a habit of staying current with advances in the field

Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem

Strong communication skills and the ability to synthesize complex algorithmic ideas for senior and external stakeholders, and to secure buy-in for cross-team work

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

Technologies we use: 

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 join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target base comp range for this position is $236,000 – $260,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In 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.

Fraud and Security Notice: 

Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com.

Equal Employment Opportunity:

Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com. 

Source: Garnerhealth careers (Greenhouse)

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