Senior Health Data Phenotyper, Center for Biomedical Informatics and Biostatistics (CB2)

The Center for Biomedical Informatics & Biostatistics (CB2) seeks an experienced Healthcare Digital Phenotyper to join the Health Data Science Services (HDSS) Team. This position will work closely with the Banner Research Warehouse team and other clinical partners to enable rapid and accurate delivery of research data for University of Arizona Researchers. This position will: design, implement, maintain, and improve digital phenotyping tools and methods; develop training materials to improve phenotype expertise across UA; and, oversee improvements in research data access across the Banner/UA collaboration.

Outstanding UA benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to UA recreation and cultural activities; and more!

The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.

• Serves as a leader and key contributor on phenotyping and data pipeline components of UAHS scientific research. Supports the technical functions, development and improvements to the digital phenotyping pipeline to UA's clinical partners. Analyzes methods and research data delivery processes at the Banner / UA interface to ensure time and cost goals are reached. Collaborate with other IT groups in Banner and UA on improvements to health research data handling in UAHS. Develops and modifies phenotype pipeline procedures and associated documentation. Recommends and implements process improvements.
• Develop and implement a training program to improve the knowledge and skills of UA researchers in the areas of phenotyping and and analysis of clinical data. Provide consultations to researchers and projects on digital phenotyping and research data handling. Ensures that current phenotyping follows current best practices.
• Utilizes in-depth knowledge of phenotyping processes, policies, and regulations to coordinate and administer various phenotyping programs or initiatives Support the HDSS team in implementing, maintaining and improving the Honest Broker functions, software and infrastructure. Develops data pipelines. Conducts quality assurance analyses on data sets. Performs deidentification and data shifting activities. May supervise 1-2 individuals as phenotyping team grows over time.
• Monitors and troubleshoots research data requests from our clinical partners. Develops improved monitoring processes and tools. Develops, updates, and maintains documentation including drawings and schematics for the phenotyping pipeline. . Facilitates solutions to bottlenecks. May represent the CB2 on university committees to initiate change and to resolve issues as a subject matter expert. Provides guidance and oversight on data and phenotyping pipelines to various projects throughout UAHS.
• Works with IT at UA and our clinical partners to ensure that phenotyping activities meet the highest standards for data privacy and security. Applies and interprets HIPAA standards to project data sets. Works closely and collaboratively with CB2 and UAHS leadership to fully understand relevant policies and procedures to provide guidance to departments, colleges, or UA. Advises projects on compliance strategies.

Knowledge, Skills, and Abilities:

• Thorough knowledge of digital phenotyping methods and strategies.
• Knowledge of programming languages used for phenotyping, such as Python, R, or SQL. Knowledge of HIPAA and other healthcare privacy and security standards.
• Ability to communicate and collaborate effectively with researchers from a wide variety of clinical and scientific domains.
• Exhibits ability to transfer knowledge and application of complex principles, theories and concepts to peers.

• Bachelor's degree in data science, computer science, biomedical or health informatics, or closely related field, or equivalent advanced learning attained through professional level experience required.
• Minimum of 8 years of relevant work experience, or equivalent combination of education and work experience.

• Masters or doctoral training in Biomedical Informatics,
• Clinical Informatics, or Health Data Science a plus.
• Experience with OMOP or other common data models a plus.
• Experience in a major phenotyping-heavy project (e.g. OHDSI, All of Us, N3C, etc) a plus.
• Knowledge of clinical terminologies (e.g. ICD, CPT, SNOMED) preferred.
• Experience querying EHR data repositories or clinical data warehouses a plus.
• Knowledge of machine learning and other advanced phenotyping approaches a plus.
• Formal clinical training and/or experience in a healthcare setting a plus.
• Experience in secondary clinical data analysis a plus.

Keith Norton, keithnorton@arizona.edu