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Senior Principal Applied Scientist
2 months ago
We are seeking a highly skilled Senior Principal Applied Scientist to modernize Oracle Life Sciences Safety One portfolio with AI native applications.
Key Responsibilities- Work with Engineering team for training data acquisition and data analysis.
- Define and follow the process for ML use case evaluation and planning.
- Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and integration of structured data, ontologies, knowledge graphs, or other forms of structured knowledge representation.
- Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.
- Explore, fine-tune, and optimize large language models such as Cohere for specific use cases in the life sciences.
- Evaluate model performance, interpret results, experiment with various training strategies, and domain-specific fine-tuning to improve accuracy and efficiency.
- Implement and experiment with cutting-edge NLP, NLU, and NLG techniques to solve various use cases.
- Collaborate with engineers to integrate machine learning models into production systems, ensuring scalability, reliability, and performance.
- Interact with product and service teams to identify questions and issues for data analysis and experiments.
- Master's degree or PhD in Computer Science, Engineering, Mathematics, or related experience.
- 10+ years of experience in data science.
- Strong programming skills in Python, SQL, and proficiency with machine learning libraries such as TensorFlow, PyTorch, or R.
- Experience with cloud platforms (e.g., AWS, OCI) and containerization technologies (e.g., Docker, Kubernetes).
- Solid understanding of NLP fundamentals and experience with NLU/NLG techniques such as sentiment analysis, entity recognition, and text generation.
- Preference for expertise in developing RAG models, working with vector databases, and fine-tuning large language models.
- Experience in life sciences and healthcare domain and experience in a complex global organization is a plus.
- Excellent problem-solving abilities and a pragmatic approach to building scalable and robust machine learning systems.
- Strong communication skills with the ability to collaborate effectively with cross-functional teams and articulate complex technical concepts to non-technical stakeholders.
