# Applied Scientist III

**Company:** [Garner Health](https://hotfix.jobs/companies/garner-health)
**Location:** New York, NY
**Role:** ML Engineering
**Salary:** $236k – $260k/yr
**Experience:** 4+ years
**Skills:** Python, SQL, AWS, Snowflake, pandas, xgboost, PyTorch, hugging face, LLMs, Machine Learning, optimization, heuristics, claims data, Evaluation Frameworks
**Posted:** 2026-08-13

> Build and deploy algorithmic systems for high-impact healthcare problems, choosing among machine learning, optimization, heuristics, and hybrid approaches. The role requires 4+ years of relevant industry experience, strong applied problem-solving and evaluation skills, and fluency in modern ML tooling.

## Job Description

## Responsibilities
- Design, develop, deploy, and improve algorithmic systems powering healthcare products.
- Own ambiguous, high-stakes problems end to end, from problem framing and objective-function definition through production deployment and iteration.
- Translate healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks.
- Define metrics and validate solutions before release.
- Select appropriate approaches, including machine learning, optimization, heuristics, expert systems, and hybrid methods.
- Develop novel solutions and prototypes for complex problems.
- Review technical work rigorously and establish quality standards and evaluation tooling.
- Build a deep understanding of the healthcare economy and the company's role within it.

### Example initiatives
- Optimize provider tiering across geographic access and total cost of care.
- Fine-tune and productionize an LLM-based primary care experience, including evaluation, guardrails, and quality monitoring.
- Build member engagement models using claims and in-app behavior to select effective communication channels and timing.

## Requirements
- **4+ years** of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or **2+ years** with a relevant advanced degree.
- PhD preferred.
- Strong applied problem-solving skills and ability to define and improve meaningful metrics.
- Fluency across data and algorithmic methods.
- Strong judgment in selecting statistical models, heuristics, optimization, and simpler algorithmic approaches.
- Strong communication skills, including explaining complex algorithmic ideas to senior and external stakeholders and securing cross-team alignment.
- Bias toward action and ability to rapidly turn ideas into working prototypes.

## Technologies
- Python
- SQL
- AWS
- Snowflake
- pandas
- XGBoost
- PyTorch
- Hugging Face
- Modern LLM tooling and evaluation frameworks

## Compensation and Benefits
- Target base compensation: **$236,000–$260,000**.
- Equity incentive plan.
- Flexible paid time off.
- Medical, dental, and vision plan options.
- 401(k) with company match.
- Flexible spending accounts.
- Teladoc Health.

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