Senior Applied Scientist

Oracle Health Data Intelligence (HDI) is building AI-powered solutions that help healthcare organizations improve population health. We are seeking a Senior Applied Scientist to develop AI capabilities, with an emphasis on large language models, agentic systems, model post-training, and evaluation.
This is a hands-on individual contributor role for a scientist with strong programming skills and a practical approach to experimentation. You will develop models, build agents, and implement training and evaluation workflows, working with scientists and engineers to deliver reliable, production-ready systems.
Minimum Job Qualifications
Education and/or Experience:
8 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Bachelor's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 4 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Master's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 2 year of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field.
Job Skills:
Same skills as prior level.
Programming Language:
2 years of experience in applicable programming language.
Preferred Job Qualifications
Education and/or Experience:
9 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Bachelor's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 5 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Master's Degree in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 3 years of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field
OR
Doctorate in Mathematics or Statistics, Computer Science, Data Science, Physics, or related field AND 1 year of experience in data science, machine learning, artificial intelligence, natural language processing, speech recognition, statistical modeling, data mining, or related field.
What You’ll Do
Develop AI/ML components from data preparation and experimentation through deployment and monitoring.
Build and improve LLM-based agents incorporating retrieval, tool use, reasoning, and orchestration.
Apply model post-training techniques, including supervised fine-tuning and preference optimization, with guidance from experienced scientists.
Prepare and validate datasets for training, evaluation, and continuous improvement.
Implement and extend agent and evaluation harnesses for reproducible experimentation, trace analysis, benchmarking, and regression testing.
Measure model and agent quality, reliability, safety, latency, and cost using established evaluation methods.
Conduct error analysis and controlled experiments to identify failure modes and validate improvements.
Write maintainable, production-quality Python code with appropriate testing and documentation.
Work with engineers to integrate models and agents into production systems.
Collaborate with product, clinical, and data partners to understand requirements and interpret results.
Participate in technical discussions, design reviews, and code reviews.
Explore relevant research and assess its usefulness through practical experiments.
Basic Qualifications
Master’s or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience.
3+ years of relevant experience applying machine learning, data science, or AI to real-world problems, including relevant doctoral research.
Strong Python programming skills, including experience writing tested, maintainable software.
Hands-on experience developing LLM-based applications involving retrieval, structured outputs, tool use, or agents.
Experience training or fine-tuning machine learning models and evaluating their performance.
Experience creating evaluation datasets, implementing metrics, and conducting reproducible experiments.
Solid understanding of machine learning, optimization, statistical inference, and experimental design.
Experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent tools.
Ability to independently complete well-defined technical work and collaborate on broader initiatives.
Strong written and verbal communication skills.
Preferred Qualifications
Experience with LLM post-training, including supervised fine-tuning, preference optimization, or reinforcement learning.
Experience implementing or extending agent harnesses, tool integrations, tracing, and automated evaluations.
Experience with synthetic data generation and human or AI feedback.
Experience deploying models or agents and monitoring their performance.
Familiarity