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Data Scientist

Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)Dubai, UAE1 months agoMid-Seniorfulltime
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About This Role

Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU; www.mbru.ac.ae) is part of Dubai Health, the first integrated academic health system in the UAE. Dubai Health seeks to strengthen Dubai as a global leader in health care, medical education, research, and scientific innovation, to enhance the capabilities of Dubai’s healthcare sector. Dubai Health is managing and operating 54 sites, including 6 government hospitals, 26 ambulatory health centers, 20 medical fitness centers, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), and Al Jalila Foundation. HBMCDM offers three-year Master of Science /Residency programs , open to all nationalities, with English as the language of instruction. The college is affiliated with the Dental Hospital and other Dubai Health dental facilities, where students receive their clinical training.

HBMCDM works in close partnership with Dubai Health dental facilities, forming an integrated Oral Health Ecosystem that connects clinical care, education, research, and community engagement.

Position description:

This is a technical, hands-on role focused on data engineering, analytics, modeling, and visualization. The post holder will work closely with clinicians, educators, researchers, and system leaders to translate data into actionable insights.

Salary, rank, and tenure will be commensurate with experience and qualifications .

Essential Selection Criteria:

  • Master’s degree (or higher) in:
  • Data Science
  • Statistics
  • Computer Science
  • Biomedical / Health Informatics
  • Applied Mathematics or related discipline
  • Strong proficiency in Python for data analysis and modeling.
  • Advanced SQL skills and experience working with relational databases.
  • Solid grounding in statistics and machine learning (e.g., regression, classification, clustering, time-series analysis).
  • Experience with data visualization and dashboards (e.g., Power BI, Tableau, or equivalent).
  • Ability to build reproducible analytical workflows (version control, documentation, testing).
  • 3–6 years’ experience in a data science, analytics, or applied research role.
  • Experience working with complex, real-world datasets (healthcare, education, or research data preferred).
  • Demonstrated ability to translate stakeholder questions into analytical solutions.

Desirable Attributes:

  • Experience working with health or clinical data (EHRs, outcomes data, registries).
  • Familiarity with data governance, privacy, and confidentiality in regulated environments.
  • Exposure to:
  • Predictive modeling and forecasting
  • Optimization or operational analytics
  • Text, imaging, or omics data (advantageous but not required)
  • Experience supporting research projects , publications, or grant-funded studies.
  • Familiarity with cloud-based analytics platforms (e.g., Azure, AWS, GCP).

Key Responsibilities:

  • Develop and maintain analytics pipelines for clinical, education, and research datasets.
  • Build dashboards and visualizations to support operational, academic, and research decision-making.
  • Perform statistical analyses and machine learning to identify trends, patterns, and opportunities for improvement.
  • Work closely with clinicians, faculty, and administrators to understand analytical needs.
  • Support research projects with data preparation, analysis, and publication-ready outputs.
  • Contribute to cross-functional analytics initiatives within the Oral Health Ecosystem.
  • Ensure data accuracy, consistency, and documentation.
  • Apply best practices in data security, privacy, and ethical use of health data.
  • Support institutional standards for reproducible and auditable analytics.
  • Contribute to departmental initiatives, working groups, and task forces as required.
  • Engage in continuous professional development to stay current with data science best practices.

Application Process

Interested candidates should submit:

  • A full curriculum vitae.
  • A cover letter addressing the selection criteria.
  • Contact details for at least three referees.

Apply via Interfolio: apply.interfolio.com/181502

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