PointClickCare - (Canada) Senior Clinical Data AI Reviewer

About the role

We are looking for a dedicated Senior Clinical Data AI Reviewer to join our team in Canada. This on-site role involves reviewing, labeling, and validating clinical data to ensure accuracy and consistency, supporting the development and refinement of AI models used in healthcare. The position offers an to apply clinical expertise within a health tech environment, contributing to the advancement of AI-driven healthcare solutions. The successful candidate will collaborate closely with research staff, product teams, and other stakeholders to ensure high-quality data and model performance, ultimately helping improve patient care and provider workflows through innovative AI applications.

Key facts

What you'll do

• Review and accurately label clinical data to verify alignment and agreement among annotations, ensuring high data quality for AI model training and evaluation.
• Assist subject matter experts (SMEs), such as clinicians familiar with documentation in electronic health records (EHR), in evaluating annotations and resolving discrepancies to maintain data integrity.
• Evaluate AI model results, providing detailed feedback to improve model accuracy and reliability, especially in complex clinical scenarios.
• Collaborate with research staff, product teams, and other stakeholders to understand project requirements, clarify clinical aspects of data, and support the discovery of new data needs or improvements.
• Advocate for the clinical accuracy and quality of AI solutions by working closely with technical teams, including senior model development researchers, product leaders, and AI UX researchers/designers.
• Help resolve disputes and disagreements among clinical SMEs regarding labeled data, facilitating consensus and ensuring consistent standards.
• Support the data labeling process by performing extensive data manipulation tasks, including categorizing nuanced clinical concepts and ensuring proper documentation of review activities.
• Use data labeling software tools to annotate and process large datasets, maintaining accuracy and efficiency throughout the review process.
• Apply statistical measures to assess inter-annotator agreement, helping to maintain consistency and reliability across multiple reviewers.
• Engage with clinical workflows, documentation practices, and healthcare processes to provide SME insights that enhance AI model understanding and performance.
• Contribute to continuous improvement initiatives by providing feedback on review procedures and suggesting enhancements to data quality and model training processes.
• Participate in team meetings, training sessions, and cross-disciplinary collaborations to stay updated on project goals, new AI developments, and clinical best practices.
• Support research and development efforts by ensuring that clinical data used in AI models reflects real-world practices and standards.
• Maintain detailed records of review activities, annotations, and discrepancies to support transparency and reproducibility in data labeling.
• Assist in training new team members or SMEs on data review standards and software tools to ensure consistency across the team.
• Contribute to the development of documentation and guidelines for clinical data review processes, supporting organizational knowledge sharing.
• Stay informed about healthcare regulations, privacy standards, and ITAR considerations relevant to clinical data handling and AI development.

Requirements

• RN or NP degree with a valid current license, demonstrating professional clinical qualification.
• At least 7 years of nursing experience, with a preference for those with long-term and post-acute care (LTPAC) or management experience.
• Strong knowledge of healthcare informatics or technical skills related to clinical data management and analysis.
• Familiarity with AI phenomena such as hallucinations, omissions, and terminology including LLM, NLP, and ML concepts.
• Experience with PCC products, understanding their workflows and clinical documentation processes.
• Proficiency with data labeling and annotation software tools, with the ability to perform detailed data manipulation tasks.
• Ability to work extensively on a computer, reviewing large datasets and performing nuanced clinical assessments.
• Knowledge of statistical measures used to evaluate inter-annotator agreement, ensuring data consistency.
• Demonstrated ability to quickly learn new software, systems, and concepts relevant to AI and clinical data review.
• Strong attention to detail, organizational skills, and the ability to differentiate subtle clinical nuances for accurate categorization.
• Excellent communication skills, with the ability to engage and reach consensus among SMEs of varying specialties and levels of expertise.
• Ability to handle complex clinical concepts and translate them into precise data labels suitable for AI model training.
• Experience working in multidisciplinary teams, supporting collaborative problem-solving and quality assurance processes.

Nice to have

• Prior experience working directly with AI or machine learning models within a healthcare setting.
• Knowledge of healthcare data privacy regulations and compliance standards, including ITAR considerations.
• Experience supporting research initiatives or clinical studies involving data annotation or review.
• Familiarity with healthcare IT systems beyond PCC products, such as other EHR platforms or clinical data repositories.
• Background in healthcare quality improvement or clinical workflow optimization projects.
• Additional certifications or training related to healthcare informatics, data science, or AI applications in medicine.

Skills & tools

• Clinical expertise in nursing or advanced practice nursing roles.
• Proficiency with data labeling and annotation software tools used in healthcare data management.
• Understanding of AI phenomena such as hallucinations, omissions, and the basics of NLP, LLM, and ML.
• Strong analytical skills for reviewing complex clinical data and ensuring accuracy.
• Excellent communication and interpersonal skills for collaborating with multidisciplinary teams.
• Organizational skills for managing large datasets and maintaining detailed review records.
• Ability to adapt quickly to new software, tools, and evolving project requirements.
• Attention to detail in differentiating nuanced clinical concepts and ensuring precise categorization.

Practical notes

This position requires on-site presence in Canada, with a flexible weekday schedule. The role involves working three 8-hour shifts per week, with consideration given to employee preferences for specific days. Flexibility may be needed to meet project deadlines and business needs. Candidates should be comfortable working extensively on computers, performing detailed clinical data reviews, and collaborating with multidisciplinary teams. The position emphasizes accuracy, attention to detail, and a strong understanding of clinical workflows and documentation. Candidates should have a background in nursing or advanced practice nursing, with a focus on long-term and post-acute care, and be familiar with healthcare informatics and data annotation tools. The role offers an opportunity to contribute to innovative AI solutions that improve healthcare delivery, making a meaningful impact on patient outcomes and provider workflows.