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Strong employer brand, popular mid-level data scientist title, and metro hiring increase candidate competition.
Strong ML/AI domain focus and healthcare data preference limit cross-industry transferability.
Explicit 3+ years requirement, specialized LLM/Databricks/vector DB skills and healthcare preference.
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Design, develop, and deploy advanced data science and AI solutions, including machine learning models and large language model (LLM) applications such as AI assistants and Retrieval-Augmented Generation (RAG) systems.
Work with large-scale structured and unstructured healthcare-related datasets to build predictive models and analytics solutions supporting data-driven decisions.
Develop and maintain semantic layers, AI evaluation frameworks, and collaborate with data engineering to ensure scalable, production-ready AI systems.
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field.
Minimum 3 years of experience in data science, machine learning, or applied AI roles, including production deployment of ML or LLM-powered systems.
Proficiency in Python programming and experience with modern data platforms (e.g., Databricks, Spark, MLflow, Delta Lake).
Experience working with large-scale structured and unstructured datasets, preferably in healthcare, life sciences, or biopharma domains.
Experienced in building and deploying complex AI systems leveraging LLMs, embeddings, vector databases, and multi-step AI workflows with agentic AI frameworks.
Comfortable working with clinical and real-world healthcare data and developing AI-powered decision support or knowledge-based systems.
Capable of collaborating across technical teams and communicating technical and analytical insights effectively to diverse audiences.