Data Analyst 1

University of Miami•Miami, FL

2d•Onsite

About The Position

The University of Miami/UHealth Department of Psychiatry has an exciting opportunity for a full-time Data Analyst 1 to work in Miami, FL. The Data Analyst will play a critical role in supporting the Center for Translational Sleep and Circadian Science and The Media Innovation Lab’s research mission by managing and analyzing large-scale national datasets (e.g., All of Us, CMS), preparing data for NIH- and federally funded studies, and applying advanced statistical and machine learning techniques to informatics and health data science projects. The analyst will develop and optimize data structures, algorithms, and object-oriented programs for scalable research applications, while maintaining secure databases to support reproducibility and data integrity. Responsibilities also include transforming research software into accessible web-based tools and creating high-quality data visualizations and model evaluation flowcharts (e.g., ROC-AUC analysis across diverse populations). The analyst will contribute to cutting-edge AI and machine learning projects by critically evaluating model architectures, preprocessing techniques, and domain adaptation methods, benchmarking predictive model performance against clinical expert standards.

Requirements

Bachelor’s Degree in Software Engineering and/or Computer Science
Minimum 1 year of relevant experience required
Learning Agility: Ability to learn new procedures, technologies, and protocols, and adapt to changing priorities and work demands.
Teamwork: Ability to work collaboratively with others and contribute to a team environment.
Technical Proficiency: Skilled in using office software, technology, and relevant computer applications.
Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders.
Ability to clearly communicate research findings through oral presentation and written publication.
Ability to work independently and in a collaborative manner with a diverse group of scientists and clinicians.
Strong skills in computer science
Experience in Artificial Intelligence (Deep learning, Transfer learning, Neural networks)

Nice To Haves

Experience with AI model development
Familiarity with applying AI methods to improve health equity or assessing the impact of AI on health equity
Strong programming skills in R, Python, Bayesian machine learning, etc.
Experience using computing clusters (batch processing), cloud computing services, and containerization.
Any relevant education, certifications and/or work experience may be considered.

Responsibilities

Performs basic data analysis using various techniques, e.g. statistical analysis, explanatory and predictive modeling, data mining.
Researches best practices and supports developing the solutions and recommendations for the current business operations.
Generates reports and analyzes data for internal planning processes and reporting purposes.
Maintains databases and dashboards to support the department’s planning needs, goals, and objectives.
Provides basic business data interpretation, such as identifying trends or patterns of data sets.
Analyzes information in reports to support the department's planning, needs, goals, and objectives.
Analyzes data to ensure accuracy and reports any issues to management.
Adheres to University and unit-level policies and procedures and safeguards University assets.
Oversees data entry and verification, ensures adherence to data entry protocols.
Creates the databases related to recruitment, enrollment, and medical data.
Designs a system to perform periodic checks to ensure that procedures are followed for data entry and coding and a computerized behavioral checklist to monitor contact between participants and study staff.
Works directly with the Primary Investigators to perform all pre-planned statistical analyses.
Conducts data acquisition, management, and statistical analysis for large-scale national datasets (e.g., All of Us Research Program, NHANES, CMS claims data) to support departmental research initiatives.
Supports NIH- and federally-funded project teams by preparing analytic datasets, ensuring compliance with data use agreements (DUAs), IRB protocols, and NIH data sharing policies.
Applies machine learning techniques (e.g., supervised and unsupervised learning, natural language processing) to health and clinical data, supporting predictive analytics and precision medicine initiatives.
Develops algorithms and advanced data structures to optimize data processing workflows, particularly for large-volume, high-dimensional healthcare datasets.
Utilizes object-oriented programming (e.g., Python, Java) to develop modular, scalable research codebases for clinical informatics projects.
Designs and maintains relational and non-relational databases (e.g., PostgreSQL, MongoDB) to store and manage complex biomedical and clinical datasets.
Leads the transformation of a Python-based desktop research application into a web-accessible tool using ReactJS, HTML, and CSS, enhancing usability and accessibility for external collaborators.
Leverages GitHub for version control, continuous integration/continuous deployment (CI/CD) workflows, and collaborative project management with internal and external research stakeholders.
Creates data visualizations, AI model performance dashboards, and analytic flowcharts to communicate sensitivity, specificity, and ROC-AUC metrics across diverse demographic subgroups (e.g., skin tones, gender, age groups).
Performs technical evaluation of AI/ML architectures (e.g., DeepDerm, HAM10000) including training protocols, data preprocessing methods, and domain adaptation strategies (GroupDRO, CORAL, CDANN), benchmarking model performance against human experts.
Manages study data under the PI’s supervision and creates computerized data collection forms to ensure integrity and accuracy of data entry.