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Clinical Informaticist

Oracle -
Bengaluru, Karnataka

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Job details

Full-time
3 days ago

Qualifications

Oracle
Quality assurance

Full job description

Apply clinical and informatics knowledge to author and refine clinical algorithm requirements on the Oracle Health Data Intelligence (HDI) platform.
Interpret industry standards, specifications, and clinical documentation to draft internal algorithm requirements.
Participate in design and requirements-gathering sessions with internal teams and customer stakeholders to ensure algorithms align with clinical, regulatory, and business objectives.
Comprehend clinical workflows to guide algorithm development and enhance clinical outcomes.
Use internal tools to curate and maintain clinical terminology value sets and to map clinical data to standard terminologies.
Collaborate with engineering by handing off clearly defined algorithm requirements and documentation.
Draft comprehensive testing scenarios, including edge cases, to support validation and quality assurance processes.
Begin to develop familiarity with healthcare data models and how they impact algorithm design.

Strong critical thinking and problem-solving skills for designing, evaluating, and optimizing clinical algorithms that align with both clinical and business objectives. Proven ability to identify gaps and propose innovative solutions within complex healthcare workflows.
Comfortable working in ambiguous, fast-paced environments, with the ability to adapt quickly to evolving healthcare technologies and priorities.
Clinical Informaticists may have a wide variety of clinical backgrounds including:

Clinical Laboratory Scientist (CLS)
Registered Nurse (RN)
Medical Technologist (MT)
Medical Laboratory Scientist (MLS)
Respiratory Therapist (RT)
Physical Therapist (PT)
Mental Health Professional
Social Worker

Or relevant clinical or healthcare informatics experience.

Expected to need regular guidance in areas such as working in a service team; prioritization of tasks; making conscious trade-offs writing clear technical docs; coding for edge-cases, building models and solutions into production.

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