Healthcare Data Scientist - Machine Learning & Clinical Analytics, Dubai Festival City

Job Requisition ID: 180608 Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United Arab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world's most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organization to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate. By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day Use Data Science to Predict, Improve, and Transform Healthcare Outcomes Al-Futtaim Health is seeking an experienced Healthcare Data Scientist – Machine Learning & Clinical Analytics to join our HealthHub Corporate Office in Dubai Festival City. This is a specialist data science role focused on predictive modelling, machine learning, clinical analytics, healthcare data integration, and AI-driven decision support across our growing healthcare network. Important: This is not a Data Analyst, BI Analyst, Reporting Analyst, Power BI Developer, or dashboard-only role. We are looking for a hands-on Data Scientist who has personally built, trained, tested, and evaluated predictive models using real healthcare datasets such as electronic health records, claims, pharmacy data, laboratory data, clinical activity data, or healthcare operational data. The purpose of this role is to move beyond reporting what has already happened and help HealthHub predict what may happen next, optimise patient pathways, improve clinical decision-making, and support better healthcare outcomes. About the Role As a Healthcare Data Scientist, you will design, develop, and evaluate machine learning models and advanced analytics solutions that support clinical, operational, financial, and strategic decision-making. You will work closely with clinical leadership, medical directors, operations teams, finance, IT, health informatics, and compliance stakeholders to transform complex healthcare data into predictive insights and practical healthcare solutions. The role requires a strong combination of healthcare domain knowledge, statistical modelling, machine learning, Python or R, advanced SQL, healthcare data standards, and responsible healthcare AI practices. Key Responsibilities 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. Essential Requirements Currently 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 acti

Essential Requirements: Currently 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, and healthcare operational data.

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.