- Company Name
- Oscar Health
- Job Title
- Senior Data Scientist, Advanced Risk Modeling Data | San Francisco, California, United States
- Job Description
-
**Job Title:** Senior Data Scientist, Advanced Risk Modeling
**Role Summary:**
Lead the design, development, and deployment of advanced machine learning and artificial intelligence models to address complex risk adjustment challenges in healthcare. Utilize large, multi‑source datasets to engineer features, build predictive models (regression, classification, deep learning, NLP, gradient boosting, LLM), and operationalize them via modern ML Ops platforms. Drive continuous improvement of model performance, monitor impact, and collaborate cross‑functionally to embed solutions within business workflows.
**Expactations:**
• Deliver production‑grade models that meet accuracy, interpretability, and regulatory requirements.
• Communicate insights and technical solutions effectively to stakeholders.
• Showcase ownership of model lifecycle from ideation to deployment and monitoring.
• Stay current with cutting‑edge AI research (e.g., LLMs, agentic frameworks) and evaluate applicability to risk adjustment.
**Key Responsibilities:**
- Conduct deep data analysis and feature engineering on complex healthcare datasets.
- Design, prototype, and validate ML/AI models addressing risk adjustment problems.
- Leverage ML Ops (e.g., Vertex AI) to streamline training, testing, and deployment pipelines.
- Build and maintain infrastructure for data, analytics, and real‑time monitoring.
- Explore and experiment with advanced techniques, including LLMs and agentic AI.
- Partner with engineering, product, and business teams to translate models into operational tools.
- Identify high‑impact opportunities, translate business needs into data science solutions.
- Ensure model governance, documentation, and compliance with industry standards.
**Required Skills:**
- Strong proficiency in SQL, Python, and/or R for data manipulation and analysis.
- Experience building statistical and machine learning models (regression, classification, gradient boosting, deep learning, NLP).
- Familiarity with ML Ops and cloud platforms (e.g., Vertex AI, GCP, AWS).
- Ability to interpret and explain model results to non‑technical stakeholders.
- Knowledge of healthcare or insurance domain data and terminology.
- Strong analytical, problem‑solving, and communication skills.
**Required Education & Certifications:**
- Advanced degree (Master’s or PhD) in Data Science, Statistics, Computer Science, Engineering, or related quantitative field.
- Professional certifications in data science or machine learning (e.g., Coursera, Udacity, Google Cloud, AWS) preferred but not mandatory.
San francisco, United states
On site
Senior
26-12-2025