Research Informatics Analyst- Winship Cancer Institute

About the role

Winship Data and Technology Shared Resource seeks a highly motivated Research Informatics Analyst to support cancer-focused translational, clinical, and population research across Winship Cancer Institute.

Responsibilities

• Serves as a key component of the shared resource infrastructure, providing centralized informatics and analytic expertise to investigators conducting cancer research across discovery, translational, and clinical domains.
• Engineering scalable and reusable analytic datasets that support research reporting, cohort identification, feasibility analyses, and advanced analytics, with dedicated support for the Myeloma Research Team.
• Designs curated data models, develops optimized and maintainable SQL logic, and produces standardized data extracts that enable consistent downstream use across research and analytic workflows.
• Leverages Epic analytics certifications and training grounded in Epic Cogito, with preferred experience aligned to Epic data environments such as Clarity, Caboodle, and Cosmos, as well as experience supporting automation, machine learning, and emerging data science initiatives.
• Contributes to project feasibility analyses, aggregate-level reporting, dashboarding, and the development of reproducible, well-documented analytic workflows.
• Operates within a regulated research environment and ensures rigor, transparency, and responsible data use within cancer research.

Qualifications

• A bachelor's degree and five years of experience in information technology or an equivalent combination of education, training and experience which includes experience working within a health, research, or academic institution.
• Knowledge of data and information systems standards relevant to the field of biomedical informatics and health systems.
• Master’s degree in informatics, data science, analytics, public health or a related field, or an equivalent combination of education and experience.
• Demonstrated experience working with large, complex research or clinical datasets in an academic or healthcare setting.
• Demonstrated project management skills, including coordinating analytic work, managing timelines, and collaborating across technical, clinical, and research teams.
• Strong working knowledge of relational database design with advanced proficiency in SQL for developing complex queries and data extracts, along with experience using analytic or informatics tools such as SAS, R, and Python.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Familiarity with research data governance, regulatory requirements, and best practices for documentation and reproducibility.
• Experience supporting automation, machine learning, and AI-enabled analytics is highly desirable, including development of scalable data pipelines and research-ready datasets that support advanced analytic and computational workflows.