Data Science Analyst
Listed on 2026-02-16
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IT/Tech
Data Analyst, Data Scientist
Overview
Job Title: Data Science Analyst 2
Location: Augusta University
Regular/Temporary: Regular
Full/Part Time: Full-Time
Job : 294609
Augusta University is Georgia's innovation center for education and health care, training the next generation of innovators, leaders, and healthcare providers in classrooms and clinics on four campuses in Augusta and locations across the state. More than 12,000 students choose Augusta for educational opportunities at the center of Georgia's cybersecurity hub and experiential learning that blends arts and application, humanities, and the health sciences.
Augusta is home to Georgia's only public academic health center, where groundbreaking research is creating a healthier, more prosperous Georgia, and world-class clinicians are bringing the medicine of tomorrow to patient care today. Our mission and values are described at the Augusta University website.
Location addresses:
Augusta University Health Sciences Campus, 1120 15th Street, Augusta, GA 30912;
Summerville Campus, 2500 Walton Way, Augusta, GA 30904.
Summary: The Department of AI & Health seeks an experienced Data Scientist 2 to join our research unit and provide technical leadership in advancing computational health research capabilities. This mid-level role combines hands-on data science with team leadership to establish our department as a leader in AI-driven health research. The role leads complex research projects involving medical imaging, electronic health records, genomics, and real-time patient monitoring data, mentors team members, and contributes to a growing portfolio of high-impact research in predictive diagnostics, personalized medicine, and clinical decision support systems.
Responsibilities- Application Development and System Design
Contribute to the design, development, and implementation of software solutions across the full development lifecycle. - Collaborate with team members to ensure solutions are scalable, secure, and aligned with organizational goals.
- Analyze complex problems and propose innovative, practical solutions that support research and operational needs.
- Adapt to evolving technologies and methodologies to deliver high-quality applications that advance health and AI initiatives.
- Application Implementation and Maintenance
Support the deployment, maintenance, and enhancement of applications and databases to meet user and project requirements. - Work closely with stakeholders to understand needs, translate requirements into actionable plans, and ensure systems operate reliably and efficiently.
- Document processes and workflows to promote clarity, consistency, and knowledge sharing across teams.
- Communication
Engage effectively with technical and non-technical audiences to gather requirements, share progress, and provide guidance. - Contribute to user documentation and training materials to enhance usability and adoption.
- Foster a culture of collaboration by supporting team members, addressing challenges, and promoting continuous improvement.
- Supervision and Leadership
Provide mentorship and guidance to junior developers, encouraging professional growth and skill development. - Lead by example in promoting best practices, problem-solving, and adaptability within the team.
- Required
Bachelor's degree from an accredited college or university in Data Science, Computer Science, Biomedical Informatics, Statistics, Engineering, or a related field with three years of related experience. - Preferred Qualifications
Prior involvement in healthcare, academic operations, or public sector analytics. Familiarity with EHR systems (Epic, Encompass) or academic admissions systems (AMCAS). - Preferred Experience
Demonstrated experience with machine learning, natural language processing (NLP), or AI model development. - Knowledge, Skills, & Abilities
Experience working with clinical, academic, or institutional datasets preferred. Advanced knowledge of Microsoft, open-source, and web standard technologies. Proficiency in Python, R, and data manipulation libraries (e.g., pandas, scikit-learn, Tensor Flow/PyTorch). Excellent communication skills and ability to translate complex technical findings for non-technical…
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