Manager, Data Science - Informatics and Health Data Science

Manager, Data Science

The University of Miami/UHealth Department of Informatics and Health Data Science has an exciting opportunity for a full time Manager, Data Science to work in Miami, FL.

The Manager, Data Science supports the Department Chair in managing and coordinating data science initiatives across the Department of Informatics and Health Data Science (DIHDS) and the Media and Innovation Laboratory (The MIL). The Manager applies advanced analytics, artificial intelligence, machine learning, predictive modeling, and related data-driven technologies to support the department's strategic priorities across Research, Education, Clinical Innovation, Service/Outreach/Policy/Ethics, and Venture.

A major departmental priority is the development and implementation of large-scale, multidisciplinary research initiatives supported by the National Institutes of Health (NIH), the Advanced Research Projects Agency for Health (ARPA-H), and other federal, foundation, and industry sponsors. The Manager works closely with the Chair, faculty, investigators, engineers, technical teams, and collaborators across the University of Miami to address the data architecture, integration, analytics, modeling, infrastructure, and reporting requirements of complex, multi investigator, and multi-institutional projects.

The Manager also supports key departmental engineering and innovation initiatives, including the continued development, implementation, evaluation, and advancement of the MIL Agentic Data Scientist (MILADS) and other AI-enabled research tools. In collaboration with departmental leadership and internal and external partners, the Manager contributes technical expertise to the development, validation, translation, and potential commercialization of innovative products and technologies.

Core responsibilities:

• Conducts initial assessments and data analyses to identify and quantify/qualify recommended opportunities for improvement.
• Serves as a business change agent leading process re-engineering activities/project.
• Manages the daily activities of the team responsible for identifying business trends and problems through big data analysis.
• Oversees the interpretation of results using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining.
• Manages the design and implementation of big data solutions for the organization utilizing big data tools.
• Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high-volume data from a variety of sources.
• Develops infrastructure systems that connect internal data sets.
• Manages analysis of large quantities of data and presents insights and predictions to support management planning, execution and monitoring of business decisions.
• Manages team, budget, and project staffing assignments.
• Establishes and continuously assesses the effectiveness of the internal controls within the unit and compliance with University policies and procedures.
• Ensures employees are trained on controls within the function and on University policy and procedures.

Department Specific Functions:

• Manages and coordinates the department's data science portfolio in alignment with the strategic priorities of DIHDS, The MIL, the Miller School of Medicine, and the University of Miami.
• Works closely with the Department Chair, faculty, investigators, engineers, and research teams to translate scientific, operational, and population-health questions into defined data science projects, analytical plans, technical requirements, and measurable outcomes.
• Supports the development of large-scale NIH, ARPA-H, and other externally sponsored proposals by contributing to study design, data strategies, preliminary analyses, technical plans, analytic workflows, infrastructure requirements, budgets, and related application components.
• Provides ongoing data science and analytical support for funded studies, including data acquisition, ingestion, cleaning, harmonization, integration, documentation, analysis, visualization, and reporting.
• Manages data science personnel, analysts, consultants, and other technical contributors assigned to departmental research, education, engineering, and innovation initiatives.
• Coordinates the development and application of advanced analytical methods, including statistical analysis, predictive modeling, machine learning, classification, time-series analysis, causal inference, feature engineering, and…