As a leading health insurance marketplace, Go Health's mission is to improve access to healthcare in America. For customers, enrolling in a health insurance plan is confusing and difficult, and seemingly small differences between plans can lead to significant out-of-pocket costs or lack of access to critical medicines and even providers. We use our technology, data science, agents, and expertise to cut through the confusion and get customers enrolled in a plan with the right coverage and benefits.
Requirements
- 3+ years of hands-on experience in building and deploying predictive ML models (e.g., logistic regression, LGBM, time-series forecasting).
- Strong statistical and mathematical background, including experience with A/B testing, bootstrapping, sampling, and Bayesian methods.
- Experience building and shipping production ML and/or GenAI systems, with awareness of architectural and operational considerations.
- Expertise in Python and proficiency in SQL.
- Experience working in a cloud ecosystem like AWS (e.g., SageMaker, ECS, Lambda, S3) or Databricks.
- Ability to move rapidly from prototype to production with well-documented, testable code.
- Familiarity with ML observability and monitoring tools, and designing systems that track both model performance and business value.
Responsibilities
- Design, develop and deploy ML/AI systems that solve core business problems—ranging from predictive modeling (e.g., acquisition, conversion, retention) to GenAI-powered tools (e.g., embeddings, retrieval-augmented generation).
- Build and scale ML systems end-to-end: from feature/data engineering to training, evaluation, deployment, and monitoring.
- Productionalize models using modern software engineering practices: version control, unit testing, CI/CD, scalable APIs, logging, and alerting.
- Collaborate cross-functionally with Product, Engineering, and Business teams to turn ideas into measurable value-driving ML features and services.
- Establish robust evaluation and monitoring frameworks to ensure model performance, drift detection, and business impact measurement.
- Contribute to the evolution of GoHealth's AI/ML platform and best practices.
- Mentor junior engineers and contribute to a culture of innovation and continuous learning.
Other
- We are looking for builders who will contribute to the long-term health of the company.
- Ability to collaborate cross-functionally and communicate complex ML/AI concepts to technical and non-technical stakeholders.
- Experience with GenAI tools and techniques, such as LLMs, prompt engineering, embeddings, or RAG workflows.
- Familiarity with agentic AI workflows, real-time streaming pipelines, or feature store architectures.
- Experience in healthcare, consumer, financial or investment mgmt. industries.
