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Role Overview:
- Transform messy unstructured EHR data into scalable healthcare data products
- Drive clinically meaningful machine learning systems for real-world evidence generation
- Support Verana Qdata products and commercial projects with fit-for-purpose approaches
What You'll Do:
- Fine-tune, deploy, and monitor pretrained language models for healthcare applications
- Collaborate with Product, Engineering, Medical, and Commercial teams on data analytics requirements
- Mentor team members in machine learning and NLP best practices
Qualifications:
- Doctorate plus 3+ years or Master's plus 5+ years in a quantitative discipline
- Experience with transformer architectures, LLMs, and messy clinical data
- Strong Python, PySpark, R, SQL skills and familiarity with Databricks and SageMaker
Verana Health
Verana Health is a digital health company that delivers quality drug lifecycle and medical practice insights from an exclusive real-world data network in ophthalmology, neurology, urology, and oncology. Backed by Johnson & Johnson Innovation and GV, the company recently raised $150 million in Series E and maintains a diverse, remote-friendly culture with offices in San Francisco, New York City, and Knoxville.