Healthcare Data Scientist - Machine Learning & Clinical Analytics

• Build, train, test, and evaluate predictive machine learning models for healthcare use cases.

  Develop models that support clinical risk prediction, patient outcomes, utilisation, readmission risk, claims analytics, revenue cycle optimisation, and care pathway improvement.

  Analyse and model healthcare datasets including EHR, clinical, claims, pharmacy, laboratory, patient activity, and healthcare operational data.

  Apply statistical and machine learning techniques such as logistic regression, survival analysis, classification, clustering, random forest, XGBoost, and other predictive modelling methods.

  Prepare analytical datasets using advanced SQL, including cohort building, joins, window functions, longitudinal patient data, feature engineering, and data quality checks.

  Work with healthcare data standards and coding systems such as ICD-10/11, CPT, SNOMED CT, LOINC, HL7, and FHIR.

  Support clinical decision support, predictive analytics, healthcare AI, and data governance initiatives.

  Collaborate with clinicians and operational stakeholders to translate data science outputs into practical healthcare workflows.

  Evaluate model performance using appropriate metrics such as AUC, precision, recall, F1 score, sensitivity, specificity, calibration, and explainability methods.

  Ensure healthcare data privacy, ethical AI use, and compliance with relevant healthcare data governance requirements.

Desired Candidate Profile

• urrently residing in the UAE.

  Bachelor’s Degree in Data Science, Computer Science, Statistics, Biostatistics, Biomedical Engineering, Health Informatics, or a related quantitative discipline.

  Minimum 2–5 years’ experience in data science.

  Minimum 2 years’ experience working with healthcare datasets, clinical analytics, health informatics, healthcare AI, health insurance data, or health-tech data.

  Proven hands-on experience building predictive models or machine learning solutions.

  Advanced Python or R experience for data science, machine learning, statistical modelling, feature engineering, and model evaluation.

  Advanced SQL experience for complex extraction, analytical dataset creation, cohort building, and healthcare data preparation.

  Experience working with healthcare datasets such as EHR, clinical, claims, pharmacy, laboratory, patient activity, or healthcare operational data.

  Understanding of healthcare coding or interoperability standards such as ICD-10/11, CPT, SNOMED CT, LOINC, HL7, or FHIR.

  Ability to communicate technical outputs clearly to clinical, operational, finance, and leadership stakeholders.

  Highly Desirable

  Master’s Degree or PhD in Health Data Science, Biostatistics, Computational Biology, Data Science, or a related field.

  Experience with UAE healthcare data environments, DHA regulations, NABIDH, Malaffi, or healthcare data residency requirements.

  Experience working within a hospital, clinic network, healthcare group, health insurance provider, health-tech company, clinical analytics team, or health informatics environment.

  Experience with clinical decision support systems.

  Experience with SHAP, LIME, or other model explainability methods.

  Experience with Power BI, Tableau, Plotly, or Dash to communicate data science outputs to leadership.