Data Science Analyst

About Us

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 https://(Use the "Apply for this Job" box below). make Augusta University an institution like no other.

The Department of AI & Health seeks an experienced Data Scientist 2 to join our research unit and provide technical leadership in advancing our computational health research capabilities. This mid‑level position combines hands‑on data science expertise with team leadership responsibilities, playing a pivotal role in establishing our department as a leader in AI‑driven health research. This role will lead complex research projects involving medical imaging, electronic health records, genomics, and real‑time patient monitoring data while mentoring team members and contributing to our growing portfolio of high‑impact research in predictive diagnostics, personalized medicine, and clinical decision support systems.

Their leadership will directly enable grant acquisition, accelerate publication output in top‑tier journals, attract doctoral students and postdoctoral fellows, and establish valuable partnerships with clinical departments and external collaborators seeking robust computational capabilities.

• Application Development and System Design:
  Contribute to the design, development, and implementation of software solutions throughout 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.

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' related experience.

• Prior involvement in healthcare, academic operations, or public sector analytics.
• Familiarity with EHR systems (Epic, Encompass) or academic admissions systems (AMCAS).
• Demonstrated experience with machine learning, natural language processing (NLP), or AI model development.
• 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,…