As an Informatics Team Member, you will work in a hybrid capacity, with a balance of remote work and in-office presence. Your role is strategically impactful, requiring you to be physically present in the office on designated days to collaborate closely with cross-functional teams. The flexibility of remote work will allow you to join late meetings that can be effectively attended outside the office while ensuring your in-office time maximizes your communication with your team.

Description of the Responsibilities of an Informatics Team Member

• Design and Strategy: Design and implement our ontology framework for symbolic data processing, with a strong emphasis on medical databases and academic research. Ensure the accurate representation of medical knowledge within the ontologies.
• Ontology Development and Maintenance: Develop and maintain ontologies while ensuring they are up-to-date and accurately reflect evolving medical knowledge and standards.
• AI Output Enhancement: Contribute to the continuous improvement of AI outputs, particularly in the analysis of medical texts, ensuring high-quality and reliable results.
• Integration of AI Techniques: Assist in projects integrating symbolic AI with machine learning models aiming to enhance the overall data analysis capabilities and provide more robust solutions.
• Documentation and Communication: Document and present findings, methodologies, and best practices to both technical and non-technical audiences. Share in the creation of cross-functional tasks' guidelines and rules.
• Product and AI Optimization: Partner with internal teams to drive improvements in product and AI quality. Support the optimization of reporting tools to better meet organizational needs.
• Validation and Process Improvement: Validate data and AI model accuracy, identifying and solving inefficiencies in current processes.
• Continuous Learning and Innovation: Stay up-to-date with the latest advancements in symbolic AI, knowledge representation, and their applications in healthcare.

Basic Qualifications

• A baccalaureate degree in a relevant healthcare field, namely medicine or pharmacy.
• Proficient use of Google and Microsoft Suite applications.
• Specialized clinical and scientific expertise relevant to clinical data, such as prior experience with real-world datasets, designing clinical algorithms or clinical phenotypes, or creating other complex logic using clinical data.
• Familiarity with healthcare data and interoperability standard terminologies. (e.g., HL7, FHIR, ICD-10, SNOMED CT, Rx Norm).
• Effectively conveys essential knowledge of diseases' processes, diagnostics, therapeutics, and other clinical data concepts.
• Strong skills in analyzing, researching, and synthesizing large amounts of data.
• Strong organizational and time management skills, with the capacity to adapt to change.

Preferred Qualifications

• Understanding and familiarity with the basics of AI, such as, but not limited to, Machine learning, Symbolic AI, LLMs, and Formal Logic.
• Python/SQL/R programming is nice to have.
• Experience in data cleaning, manipulation, visualization, and statistical analysis, particularly in the context of healthcare data.
• Ability to design, conduct, and interpret analyses to support clinical decision-making and healthcare outcomes.
• Experience with clinical ontology engineering.
• Clinical research/clinical trial operations experience.
• Familiarity with the basic principles, practices, and policies related to biomedical research and protection of human subjects.
• A Postgraduate degree, or research experience is nice to have.

Hiring Axes

Clinical Data Specialists Acumen:

• Familiarity with creating training datasets for AI model improvements.
• Solid understanding of clinical processes and various aspects of clinical management.
• Basic knowledge of clinical data abstraction and its role in healthcare.

Clinical Informatics Acumen:

• Deep understanding of current clinical care delivery and research advancements.
• Extensive experience in real-world data analytics, clinical research, and health technology solutions development.
• Solid knowledge of AI methodologies in biomedical contexts, including machine learning and symbolic AI systems.

Product and Technical Engagement:

• Ability to contribute clinical and scientific insights to product development and technical projects.
• Understanding of system design considerations, including balancing clinical accuracy, speed to market, and scalability.

Communication and Management:

• Strong verbal and written communication skills, with the ability to explain complex topics in a clear manner.
• Experience in collaborating effectively with team members and team leads.

Cultural & Mission Alignment:

• Deep alignment with Mendel's mission and a strong belief in the transformative power of AI in healthcare.
• A passionate commitment to advancing healthcare delivery and research, demonstrated by a dedication to excellence in the role.