Assistant Research Professor (Research Scholar/Series Track) (NTE), Emergency Med

The Department of Emergency Medicine is recruiting an experienced and collaborative Data Scientist to enhance and expand the department's research initiatives. The incumbent will be responsible for designing, managing, and analyzing complex data sets. Work will involve combining data sets, and employing standard and advanced statistical methods, including machine learning algorithms. The incumbent will also pursue independent research interests, secure extramural funding, and contribute to academic publications.

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!

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• Develop, manage, and maintain research databases, ensuring accuracy, integrity, and optimal integration across diverse data sources.
• Conduct comprehensive data analyses, including standard statistical methods, advanced predictive modeling, machine learning techniques, and clinical decision support systems.
• Collaborate closely with faculty, clinicians, and researchers to design, implement, and evaluate research projects.
• Contribute methodological expertise and statistical guidance to support grant proposals and academic publications.
• Actively pursue independent research interests aligned with emergency medicine, identifying potential funding opportunities and submitting competitive grant applications.
• Present findings at scientific conferences and departmental meetings.

Knowledge, Skills and Abilities

• Demonstrated expertise with statistical software (e.g., R, Python, SAS) and familiarity with database management systems (SQL, NoSQL).
• Excellent communication and interpersonal skills, with the ability to effectively collaborate in multidisciplinary teams
• Proven experience in developing and applying advanced analytical methods including machine learning, predictive analytics, and clinical decision support models.
• Strong track record or demonstrated potential for securing independent research funding.

• PhD in data science, biostatistics, epidemiology, informatics, computer science, or a related quantitative field.
• Minimum of 2-3 years of experience in data management and statistical analysis, preferably within clinical or healthcare-related environments.

• Previous experience working in emergency medicine, acute care, or healthcare research environments.

• Experience with electronic health records (EHR) systems, clinical registries, or healthcare databases.

• Publications in peer-reviewed journals demonstrating methodological rigor and relevance to healthcare research.