Tech Stack

Description

You will leverage advanced ML/AI methodologies to build and deploy models that solve complex business problems within Oscar's risk adjustment domain. Work with large healthcare datasets, modern ML platforms, and collaborate with cross-functional teams to drive impactful data science solutions.

Requirements

• 4+ years in quantitative technical fields
• 3+ years experience with SQL, R, and/or Python for data manipulation and analysis
• 3+ years building data models and using advanced analytics and statistical methods
• Experience in healthcare, finance, or insurance industries (bonus)
• Advanced degree in quantitative or technical field (bonus)

Responsibilities

• Conduct in-depth data analysis and advanced feature engineering using large healthcare datasets
• Design and validate advanced ML/AI models (regression/classification, deep learning, NLP, gradient boosting, LLMs) for risk adjustment
• Leverage ML Ops platforms like Vertex AI to deploy and maintain production models
• Build supporting data systems and monitoring infrastructure for production AI/ML systems
• Research and evaluate new AI applications including LLM and agentic frameworks