Clinical Science Informaticist
Oracle Health Data Intelligence (HDI) is at the forefront of transforming healthcare through
innovative data and AI solutions. We’re seeking a highly skilled individual contributor to join
our team in the USA. This role focuses on leveraging clinical data, machine learning (ML), and
AI technologies to drive healthcare innovation. You’ll contribute to AI-driven projects by
applying informatics techniques, statistical modeling, and annotation guidelines to improve
healthcare delivery, patient outcomes, and operational efficiency. At HDI, we are committed to
using cutting-edge technologies such as natural language processing (NLP) and predictive
analytics to revolutionize patient care and optimize healthcare systems.
Career Level - IC4
Clinical experience in roles such as a registered nurse, pharmacist, clinical laboratory
technician, respiratory therapist, or other clinical roles. Alternatively, relevant
experience may be considered in place of formal clinical certifications.
Proven experience in clinical informatics, including familiarity with clinical EHR systems
and data, as well as collaboration with healthcare professionals, IT specialists, and
business users to analyze workflows and identify opportunities for improvement.
Strong background in working with clinical data to support evidence-based decision
making, quality measurement, care coordination, and outcomes-based improvement
programs.
Hands-on experience in supporting data annotation, creating and maintaining
annotation guidelines, machine learning (ML), natural language processing (NLP), and
AI-driven projects within the healthcare domain.
Creation of evaluation frameworks for the performance AI models.
Understanding of the AI model life cycle
Experience at the intersection of statistical methods, machine learning techniques, and
generative AI and medical standards and ontologies.
Expertise in data preprocessing, feature engineering, and model development for
AI/ML applications, with a focus on clinical data integration.
Experience in defining data requirements, ensuring data readiness, and validating
annotated data for AI/ML solutions.
Proficient in working with clinical terminologies such as SNOMED CT, ICD, LOINC, and
CPT, and utilizing them in data science models and algorithms.
Familiarity with healthcare data standards such as FHIR Resources, QDM Categories,
and experience modeling clinical and administrative healthcare data for AI-driven
solutions.
Proven ability to implement quality control processes for ensuring the integrity,
reliability, and clinical relevance of data used in AI/ML applications.
Experience in working with disparate healthcare data types, including EHR, billing, lab,
eligibility, and claims data, to drive insights and improve healthcare outcomes.
Life sciences, clinical trials, and regulatory experience is a plus.
Create and curate clinical value sets composed of industry-standard terminologies
such as SNOMED CT, ICD, and CPT, ensuring alignment with data science models,
organizational data models, and algorithms.
Develop and document clear annotation guidelines to ensure they are understood by
annotation teams and data scientists.
Define data requirements and ensure integration within AI/ML-driven applications,
with a focus on data quality and model readiness.
Implement quality control processes to validate the integrity and reliability of
annotated data, ensuring suitability for AI/ML solutions.
Lead annotation review cycles and provide feedback to ensure labeling quality, while
performing regular evaluations of model predictions to identify edge cases and
improve performance.
Defining AI red teaming and guardrails in collaboration with applied scientists.
Conduct error analysis of AI model outputs.
Recognized as a subject matter expert within the team and provide mentorship to less
experienced team members.
Drive internal platform changes including data models, terminology ontologies, and
the platform rules engine to ensure data compatibility with AI/ML models.
Oversee the collection, cleaning, and pre-processing of data, ensuring datasets are
ready for analysis and model training.
Define requirements for establishing the effectiveness of AI/ML models by designing
ground truth algorithms and performance metrics for outcome validation.
Collaborate with cross-functional teams, including data scientists, annotators,
engineers, and project managers, to enhance data quality and success across AI-driven
projects.
Contribute to model evaluation and performance monitoring, ensuring data-driven
insights meet clinical objectives.
Continue to drive and implement AI driven automated processes, both within the
annotation framework and other job expectations
Skills
Strong critical thinking and problem-solving skills, particularly for designing algorithms
and models that meet clinical and business objectives within real-world healthcare data
constraints.
Experience working with disparate healthcare data including EHR, billing, lab,
eligibility, or claims data.
Expertise in clinical and administrative healthcare data modeling using industry
standards such as FHIR Resources, QDM Categories, and other healthcare data
formats.
Advanced knowledge of data science techniques including statistical analysis, machine
learning, and natural language processing (NLP).
Proficiency in programming languages such as Python, R, or SQL for healthcare data
analysis and model development.
Experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Familiarity with industry-standard terminologies such as SNOMED CT, ICD, LOINC, and
CPT, and their application in data science models.
Knowledge of care management best practices and services and their integration with
AI/ML models.
Strong ability to interpret complex clinical and business requirements, transforming
them into actionable data guidelines and annotations.
Excellent communication and collaboration skills, working effectively with data
scientists, annotators, engineers, and project managers to drive successful AI projects.
Knowledge of model evaluation metrics and ability to conduct model validation,
ensuring that AI-driven solutions deliver accurate and actionable clinical insights.
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: $91,400 to $187,000 per annum. May be eligible for bonus and equity.
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 working fewer than 20 hours per week are not eligible for vacation.
9. 11 paid holidays
10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.
11. Paid parental leave
12. Adoption assistance
13. Employee Stock Purchase Plan
14. Financial planning and group legal
15. Voluntary benefits including auto, homeowner and pet insurance
The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.
Career Level - IC4