PointClickCare - (US)Senior Clinical Data AI Reviewer

About the role

We are looking for a dedicated Senior Clinical Data AI Reviewer to join our team on a part-time basis, working at our office in the United States. This role involves applying your clinical expertise to review, label, and validate complex clinical data to support the development and refinement of AI models used in healthcare. You will collaborate closely with research staff, product teams, and technical experts to ensure that AI solutions are accurate, reliable, and aligned with clinical standards. Your work will directly contribute to improving healthcare outcomes by ensuring the quality and integrity of data used in AI-driven healthcare solutions. This position offers an opportunity to be at the forefront of healthcare technology, combining clinical knowledge with AI applications to make a meaningful impact in the industry.

Key facts

What you'll do

• Review and label clinical data meticulously, ensuring alignment and agreement across annotations to maintain high data quality standards.
• Assist subject matter experts (SMEs) in evaluating annotations, providing guidance, and resolving disputes or discrepancies related to clinical data labels.
• Evaluate model outputs and results, offering feedback to improve AI model performance and accuracy.
• Collaborate with research staff, product managers, and other stakeholders to understand project requirements, clinical workflows, and data needs.
• Educate technical teams and non-technical audiences about complex clinical aspects of AI solutions, ensuring clarity and understanding across disciplines.
• Advocate for clinical accuracy and quality assurance by working closely with senior model development researchers, product leaders, and AI UX researchers/designers.
• Support the integration of clinical workflows and documentation practices into data review processes, ensuring consistency with healthcare standards.
• Perform extensive data manipulation tasks, including data cleaning, categorization, and analysis, to support model training and validation efforts.
• Assist in identifying and resolving disputes among SMEs regarding clinical labels, fostering consensus and ensuring data integrity.
• Document data review processes thoroughly, maintaining detailed records of annotations, discrepancies, and resolutions for audit and quality purposes.
• Contribute to continuous improvement initiatives by providing insights and feedback on data labeling procedures, model evaluation, and clinical validation processes.
• Ensure compliance with healthcare data privacy regulations and standards, maintaining confidentiality and security of sensitive information.
• Support the development of training materials and guidelines for clinical data review and annotation to enhance team consistency and quality.
• Participate in team meetings and training sessions to stay updated on project developments, new tools, and best practices in clinical data review and AI validation.
• Assist in the onboarding and mentoring of new team members, sharing expertise and promoting best practices in clinical data review.
• Maintain a high level of attention to detail and organizational skills to manage multiple data review tasks efficiently.
• Use healthcare informatics tools and data labeling software proficiently to execute review tasks accurately and efficiently.
• Communicate effectively with cross-disciplinary teams, translating clinical concepts into actionable data annotations and model feedback.

Requirements

• RN or Nurse Practitioner (NP) degree with a valid, current license.
• Minimum of 7 years of nursing experience, with a preference for those with long-term post-acute care (LTPAC) and management experience.
• Strong knowledge of healthcare informatics or equivalent technical skills/background.
• Familiarity with AI phenomena such as hallucinations, omissions, and terminology like LLM, NLP, ML.
• Experience with PCC products and data labeling software.
• Ability to perform extensive data manipulation tasks on a computer for prolonged periods, demonstrating patience and precision.
• Understanding of statistical measures used to assess inter-annotator agreement and data consistency.
• Demonstrated ability to quickly learn new software, concepts, and technologies relevant to clinical data review and AI validation.
• Strong analytical skills to review nuanced clinical concepts and categorize them accurately.
• Proven ability to engage and facilitate consensus among SMEs with varying levels of expertise and specialties.
• Excellent attention to detail, organizational skills, and the ability to manage multiple tasks simultaneously.
• Effective communication skills to collaborate with multidisciplinary teams and convey complex clinical information clearly.
• Ability to work independently with minimal supervision while maintaining high standards of accuracy and quality.

Nice to have

• Prior experience working with healthcare AI, machine learning, or data annotation projects.
• Knowledge of healthcare regulations, compliance standards, and data privacy practices.
• Experience in training or mentoring clinical staff involved in data review or annotation processes.
• Familiarity with healthcare workflows and documentation practices, especially in long-term care settings.
• Exposure to healthcare data standards such as HL7, FHIR, or other relevant protocols.
• Experience with statistical analysis tools or software to support data validation and model evaluation.

Skills & tools

• Clinical nursing expertise (RN or NP)
• Data labeling and annotation software
• Healthcare informatics systems, including PCC products
• Data manipulation and analysis tools
• Basic statistical analysis knowledge
• Strong written and verbal communication skills
• Ability to learn and adapt to new software and AI tools quickly

Practical notes

This position requires working on-site at our US office with a flexible weekday schedule, totaling 24 hours per week, divided into three 8-hour shifts. Flexibility may be needed to meet project deadlines and business needs. Candidates should be prepared for extended periods of data review, requiring sustained focus and attention to detail. The role involves handling sensitive healthcare data, so adherence to data privacy and security standards is essential. Candidates should have a strong clinical background, excellent organizational skills, and the ability to collaborate effectively across teams. The position offers an to contribute to innovative healthcare AI solutions, making a tangible difference in patient care and healthcare delivery.