Principal Data Scientist

Do you want to be a part of changing healthcare?
Oracle is excited to be using our resources, knowledge, and expertise—as well as our successes in other industries—and applying them to healthcare to make a meaningful impact. As people, we all participate in healthcare, it’s deeply personal, and we put the human at the center of each of our decisions. Improving healthcare for all requires bringing unique perspectives and expertise together to holistically tackle the biggest problems in global health including physician burnout, patient access to data, and barriers to quality care. 

Oracle Health Applications & Infrastructure (OHAI) is developing patient-and provider-centric solutions rapidly and securely. We use the value of Oracle Cloud Infrastructure (OCI) to our customers as we work across patient, provider, payor, public, population health and life sciences industries. At OHAI, you will work with authorities across industries and have access to the latest technology. We apply artificial intelligence, machine learning, large language models, learning networks, and other data intelligence and analytics in an applied way, embedded into our solutions. Join us in creating people-centric healthcare experiences.

About the team:
As part of the Oracle Health Foundations Organization, you’ll help drive data science and machine learning efforts to extract insights from large-scale observability data. Your work will focus on developing models and analytical tools to detect anomalies, predict incidents, and improve product reliability and performance—enabling smarter, faster decision-making across Oracle Health.
A successful candidate will bring a passion for problem-solving, strong collaboration skills, and the ability to work closely with software engineers, product managers, and operations teams. Most importantly – we believe in a people-first approach - we want to improve the product experience for our customers while having fun doing it! Our team consists of people from a wide variety of backgrounds, and different professional and life experiences, who support each other to build things the right way and enjoy our vacation time.

•    Lead the development and deployment of advanced machine learning models to detect anomalies, predict major incidents, and optimize product reliability across Oracle Health systems.
•    Drive exploratory and diagnostic analyses on large-scale observability data (logs, metrics, traces) to uncover root causes, performance trends, and opportunities for proactive intervention.
•    Partner with engineering, product, and reliability teams to define and implement data science strategies aligned with key business and technical objectives.
•    Mentor junior data scientists and contribute to the evolution of modeling standards, best practices, and MLOps pipelines.
•    Translate complex analytical findings into clear, actionable insights through dashboards, reports, and stakeholder presentations.
•    Stay current with the latest techniques in machine learning, anomaly detection, time series analysis, and apply them in practical, scalable ways.

Requirements:
•    7+ years of experience in data science, with a strong track record of applying machine learning to solve real-world problems at scale.
•    Expertise in Python and ML frameworks such as scikit-learn, TensorFlow, PyTorch, or similar.
•    Deep understanding of statistical modeling, time series analysis, and anomaly detection techniques.
•    Hands-on experience working with large telemetry datasets (e.g., logs, metrics, traces) in cloud environments.
•    Proficient in SQL and familiar with distributed data systems and tools (e.g., Spark, BigQuery, or similar).
•    Strong business acumen and the ability to influence product and engineering decisions through data.
•    Excellent communication skills and proven experience leading cross-functional collaborations.
•    Bachelors, Master’s or PhD in Data Science, Computer Science, Statistics, or a related field strongly preferred.

Skills
•    Machine Learning & Predictive Modeling
•    Statistical Analysis & Time Series Forecasting
•    Anomaly Detection & Root Cause Analysis
•    Python (NumPy, pandas, scikit-learn, TensorFlow/PyTorch)
•    SQL & Data Exploration
•    Observability Data (logs, metrics, traces)
•    Data Visualization & Storytelling (e.g., Matplotlib, Seaborn, Plotly)
•    Cloud Platforms (OCI, AWS, GCP, or Azure)
•    MLOps & Model Deployment
•    Cross-functional Collaboration & Technical Leadership

Disclaimer:

Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.

Range and benefit information provided in this posting are specific to the stated locations