Lead Clinical Science Informaticist

Oracle

Actively hiring Posted this week Verified listing
Austin, TX Posted 2 days ago $91,400–$187,000 / year
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Salary context

Below market

How this pay compares to similar roles

Similar $168k
This role $139k
$76k most similar roles pay here $235k

This role pays less than 69% of similar roles. Most pay $135,000–$202,000 — the shaded band above. At the midpoint, this role pays about $139k versus about $168k for comparable roles.

Based on 240 similar postings.

Employer

About Oracle

Oracle Corporation is a leading multinational technology company specializing in database software, cloud computing, and enterprise software.

Oracle currently has 394 open roles on FindRole.

Listed pay typically runs $97,500–$223,400 across 299 roles with salary data.

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At a glance

TL;DR

As an individual contributor at Oracle Health Data Intelligence (HDI) in the USA, you will lead AI-driven projects by applying clinical informatics and statistical modeling to enhance healthcare delivery. Your daily tasks include creating evaluation frameworks for AI models, ensuring data quality, and collaborating with cross-functional teams to integrate industry-standard terminologies like SNOMED CT and FHIR into AI/ML applications. You’ll use advanced technologies such as TensorFlow, PyTorch, and natural language processing (NLP) to preprocess clinical data, develop predictive analytics, and improve patient outcomes. This role demands expertise in Python, R, SQL, and a deep understanding of healthcare data standards and ontologies, making it ideal for someone with 6-10+ years of experience in clinical informatics or related fields.

Skills

Python R SQL TensorFlow PyTorch scikit-learn NLP FHIR QDM SNOMED_CT ICD CPT Machine_Learning Statistical_Analysis Data_Preprocessing Feature_Engineering Quality_Control Error_Analysis AI_Modeling Clinical_Terminologies Healthcare_Data_Standards

What you'll do

  • Create and curate clinical value sets using industry-standard terminologies.
  • Develop annotation guidelines for data scientists and annotation teams.
  • Define data requirements and ensure integration within AI/ML applications.
  • Implement quality control processes to validate annotated healthcare data.
  • Lead review cycles and provide feedback on labeling quality and model predictions.
  • Oversee the collection, cleaning, and preprocessing of diverse healthcare datasets.
  • Design ground truth algorithms and performance metrics for AI/ML model validation.

What we're looking for

  • 6+ years of clinical informatics experience with EHR systems and data.
  • Expertise in machine learning, natural language processing, and AI for healthcare.
  • Proficiency in clinical terminologies like SNOMED CT, ICD, CPT for data science.
  • Strong background in statistical methods, model development, and feature engineering.
  • Experience in defining data requirements and validating annotated data for AI/ML.
  • Ability to implement quality control processes for AI/ML application integrity.
  • Knowledge of healthcare data standards such as FHIR Resources and QDM Categories.

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