Principal Applied Scientist

Oracle Health Data Intelligence is building AI-powered products that help healthcare organizations make better, faster, and more informed decisions. We are seeking a Principal Applied Scientist to lead the development of scalable machine learning and AI solutions across a broad range of product and platform challenges. This is a hands-on technical leadership role for an experienced scientist who can turn ambiguous, high-impact business and customer problems into robust, production-ready models and systems. The role is broadly focused on applied AI/ML—not limited to a single technique such as LLMs—and has a strong engineering and coding bar comparable to a senior/principal Applied Scientist role. What You’ll Do • Lead the end-to-end development of machine learning and AI solutions: problem formulation, data analysis, feature development, modeling, offline evaluation, experimentation, deployment, and monitoring. • Design and build high-quality, maintainable production code in Python and related technologies. Write scalable, testable software rather than research-only prototypes. • Apply appropriate techniques across machine learning, deep learning, NLP, information retrieval, ranking, forecasting, anomaly detection, optimization, generative AI, and LLM-based systems. • Develop evaluation frameworks that measure model quality, reliability, safety, fairness, latency, and business or clinical impact. • Drive rigorous experimentation, including experiment design, statistical analysis, error analysis, ablation studies, and root-cause investigation. • Partner with software engineers to productionize models, define service interfaces, improve inference performance, and establish monitoring and retraining workflows. • Work closely with product, data engineering, clinical domain, security, and compliance partners to translate real-world needs into durable AI capabilities. • Set technical direction for complex initiatives, make sound tradeoffs under ambiguity, and influence roadmap decisions through data and scientific judgment. • Mentor applied scientists and engineers through design reviews, code reviews, technical guidance, and modeling best practices. • Stay current with relevant research and evaluate emerging methods pragmatically, adopting innovations when they create measurable product value. Basic Qualifications • PhD in Computer Science, Machine Learning, Statistics, Operations Research, a related quantitative field, or equivalent practical experience; OR a Master’s degree with 6+ years of relevant industry experience. • 8+ years of experience applying machine learning, data science, or AI techniques to real-world product or business problems. • Strong programming ability in Python, including writing clean, efficient, production-quality code with appropriate testing and documentation. • Experience building and shipping machine learning systems, including data pipelines, training workflows, inference services, evaluation, and model monitoring. • Deep understanding of core machine learning concepts, such as supervised and unsupervised learning, optimization, representation learning, model selection, experimentation, and statistical inference. • Experience with one or more ML frameworks such as PyTorch, TensorFlow, JAX, scikit-learn, Spark, or equivalent tools. • Demonstrated ability to independently lead ambiguous technical projects and influence cross-functional stakeholders. • Strong written and verbal communication skills, including the ability to explain technical decisions to technical and non-technical audiences. Preferred Qualifications • Experience with generative AI, large language models, retrieval systems, RAG, agentic workflows, or model fine-tuning and evaluation. • Experience with NLP, search, recommendation, ranking, time-series modeling, causal inference, or optimization. • Experience designing AI systems for high-reliability, privacy-sensitive, regulated, or customer-facing environments. • Experience with cloud-scale distributed systems and ML platforms. • Experience mentoring senior technical contributors and raising engineering and scientific standards across a team. • Healthcare, life sciences, enterprise SaaS, or similarly complex-domain experience. Level: IC4 Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $126,200 to $264,100 per annum. May be eligible for bonus, equity, and compensation deferral. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees wor