About the role
BeOne Medicines USA, Inc. is seeking an AI Innovation Intern to contribute to the integration and enablement of AI-driven platforms. The role involves supporting initiatives leveraging advanced AI models and machine learning techniques to extract insights from large datasets, ultimately impacting commercial and medical strategies in oncology.
Responsibilities:
Assist in building and implementing AI-driven analytics frameworks to generate real-time insights from structured and unstructured data.
Support the development and optimization of Retrieval-Augmented Generation (RAG) models to improve decision-making.
Conduct research and proof-of-concept projects on agentic AI and autonomous AI agents that enhance business intelligence.
Leverage machine learning and natural language processing (NLP) techniques to analyze oncology-related datasets.
Work with vector databases (e.g., Pinecone, FAISS) to improve AI-driven knowledge retrieval.
Collaborate with cross-functional teams, including Commercial, Medical, and IT, to identify opportunities for AI application.
Assist in evaluating new AI methodologies, tools, and platforms to enhance BeiGene's AI capabilities.
Present findings and AI-driven recommendations to the Advanced Analytics team and key stakeholders.
Qualification:
Currently pursuing an advanced degree with a concentration in Life Sciences, Data Science, Statistics or Engineering.
Experience or coursework in machine learning, deep learning, NLP, and data analytics.
Excellent analytical skills and the ability to translate the data and learning into actionable recommendations for business growth.
Familiarity with healthcare databases, including claims, specialty pharmacy, and in-office dispense, and electronic health records (EHR) datasets.
Prior experience in healthcare analytics, real-world data analysis, or business intelligence within the pharmaceutical or biotech industry.
Strong understanding of oncology treatment landscapes, particularly in hematologic malignancies.
Demonstrated attention to detail and excellence in project management, including effectively managing multiple projects/priorities.
Excellent interpersonal, oral and written communication skills, including ability to synthesize findings and deliver a clear overview of recommendations.
Proficiency in programming languages such as Python, R, or SQL for data analysis.
Advanced proficiency in Microsoft Excel and PowerPoint for reporting and presentations.
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