Manager, Applied Science

Doist; New York (NY); On-site; USD 300,000 - 390,000; Full time

Benefits offered by this job

Flexible PTO

Medical/Dental/Vision

401(k) with company match

Flexible spending accounts

Equity incentive plan

Job summary

Garner Health is seeking a Manager of Applied Science to build and lead a team that owns production systems end-to-end. You will frame problems, define objectives, choose approaches, ship solutions, and measure real-world outcomes in a healthcare context.

You will guide a squad of scientists, set the roadmap, and stay hands-on to ensure rigor and impact. Excellent communication and a drive to move quickly are essential as we scale AI to improve care and costs.

Qualifications

• 6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent.
• 4+ years of industry experience with a relevant advanced degree, PhDs preferred.
• Deep technical credibility with the ability to lead scientists who are experts in their own right and stay hands-on.
• Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods.
• Strong applied problem-solving skills, with the ability to define good metrics and deliver solutions that improve them.
• Bias toward action, quickly translating ideas into working prototypes to test approaches.
• Strong communication skills, including at the executive level, with a track record of driving alignment across teams.

Responsibilities

• Lead a team of Applied Scientists—hire, coach, and develop them, uphold rigor and speed.
• Own your team's roadmap and delivery: what gets built, in what order, and whether it ships.
• Set technical direction and stay close to code and data to guide the approach.
• Define metrics to judge solution effectiveness and validate results before ship.
• Work on high-stakes, ambiguous problems and deliver algorithmic step-changes that improve metrics.
• Translate ambiguous business goals into clear problem statements with Research, Product, Engineering, and stakeholders.
• Set the quality bar, review work with rigor, and define success metrics.
• Build a deep understanding of the healthcare economy and Garner's role in it.
• Turn strategic goals into concrete problems and present outcomes to senior leadership.
• Collaborate to ensure alignment across teams and functions.

Skills

Team leadership

Applied ML

Problem-solving

Metrics design

Executive communication

Hands-on engineering

Python

Education

Master's or PhD in a relevant field

PhD preferred

Tools

Python

SQL

AWS

Snowflake

Pandas

XGBoost

PyTorch

HuggingFace

Job description

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 Manager, 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. 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. 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.

Where you will work:

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.

What you will do:

Lead a team of Applied Scientists — hire, coach, and develop them, hold the bar on both rigor and speed, and help raise that bar across Applied Science.

Own your team's roadmap and delivery: what gets built, in what order, and whether it ships.

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.

Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship.

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.

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.

Set the quality bar: review your team's work with rigor, and define the metrics that decide whether a solution is working.

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

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 trade‑off 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:

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.

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.

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

Strong applied problem‑solving skills, with the ability to define good metrics and then deliver solutions that improve them.

A bias toward action, quickly translating ideas into working prototypes to test approaches.

Strong communication skills, including at the executive level, with a track record of driving alignment across teams and functions.

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.

Compensation Transparency:

The target base comp range for this position is $300,000-$390,000. 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.

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 [e-mail].