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Garner HealthGarner HealthNew York, NY

Applied Scientist III

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.

236k – 260k/yr
On-site4+ YOEML Engineering

About the role

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.

Skills

PythonSQLAWSSnowflakepandasxgboostPyTorchhugging faceLLMsMachine Learningoptimizationheuristicsclaims dataEvaluation Frameworks

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