Clinical Data Scientist - Predictive Analytics

City, the Data Scientist will tackle questions that cannot be answered through routine dashboards or descriptive reporting alone. The position owns the analytical journey from defining a healthcare problem and preparing patient-level data to validating a predictive model and embedding its insights into clinical or business processes. Close cooperation with clinicians, informatics teams, finance, operations, technology and compliance will be central to successful delivery.

Key Responsibilities

* Frame clinical, operational and financial challenges as measurable data-science problems.
* Develop predictive models for patient outcomes, utilization, readmission and clinical risk.
* Create analytical solutions for claims performance, revenue-cycle improvement and service demand.
* Assemble modeling datasets from electronic health records, laboratory systems, pharmacy records and claims platforms.
* Use SQL to construct cohorts and link longitudinal patient encounters across multiple sources.
* Apply feature engineering methods that capture clinically and operationally meaningful signals.
* Test source data for completeness, consistency, duplication and temporal accuracy.
* Select suitable statistical techniques based on the question, sample and intended healthcare application.
* Build models using logistic regression, survival analysis, classification, clustering and ensemble methods.
* Apply random forest, XGBoost or comparable algorithms when appropriate.
* Separate training, validation and test samples using methods that protect against information leakage.
* Compare model performance through AUC, precision, recall, F1 score, sensitivity and specificity.
* Assess calibration to determine whether predicted probabilities reflect observed outcomes.
* Explain predictions through SHAP, LIME or other interpretable-machine-learning techniques.
* Review assumptions and outputs with medical experts before operational use.
* Translate model results into practical alerts, pathways or decision-support recommendations.
* Work with ICD-10, ICD-11, CPT, SNOMED CT and LOINC-coded information.
* Support integration concepts involving HL7 and FHIR healthcare data exchange.
* Develop clear visual outputs through Power BI, Tableau, Plotly or Dash when required.
* Present findings in language appropriate for clinicians, operational managers and executives.
* Maintain model documentation, version history, validation results and known limitations.
* Apply privacy, ethical artificial-intelligence and healthcare data-governance principles.
* Support compliance with UAE data-residency requirements and relevant health-authority standards.
* Monitor deployed solutions for drift, bias and declining predictive performance.

Ideal Profile

Applicants must currently reside in the UAE and possess a bachelor\'s degree in data science, statistics, computer science, biostatistics, biomedical engineering, health informatics or a related quantitative field. A postgraduate degree in health data science, computational biology, biostatistics or a similar discipline would add value.

The required background includes two to five years of data-science experience and at least two years working directly with healthcare, clinical, insurance or health-technology data. Candidates must be able to demonstrate personal involvement in building, testing and evaluating predictive models with Python or R.

Advanced SQL capability is essential. Preference will be given to applicants familiar with hospitals, clinics, insurers, clinical decision-support systems, DHA requirements, NABIDH, Malaffi or UAE healthcare data controls. Experience limited to reporting, dashboard creation, KPI monitoring or SQL extraction without statistical modeling is insufficient.

Skills Set

* Healthcare machine learning
* Clinical predictive analytics
* Python or R
* Advanced SQL
* Patient cohort construction
* Longitudinal data preparation
* Statistical inference
* Feature engineering
* Logistic regression
* Survival analysis
* Supervised and unsupervised learning
* Random forest and XGBoost
* Model testing and validation
* Calibration analysis
* Explainable artificial intelligence
* SHAP and LIME
* Electronic health record data
* Claims and payer analytics
* Pharmacy and laboratory datasets
* Revenue-cycle modeling
* ICD-10, ICD-11 and CPT
* SNOMED CT and LOINC
* HL7 and FHIR
* Clinical decision support
* Data privacy and ethical artificial intelligence
* Power BI, Tableau, Plotly or Dash
* Technical and clinical communication

Why Join Us

This role offers the chance to influence healthcare delivery through models that address real patient, clinical and operational questions. The successful candidate will collaborate with decision-makers across an expanding clinic network and contribute to the development of responsible healthcare artificial intelligence in the UAE. The position includes competitive compensation, medical insurance, career development and exposure to multidisciplinary healthcare innovation.

About the Company

Al-Futtaim Healthcare delivers outpatient and diagnostic services through the HealthHub Clinics network in Dubai. Its more than 20 clinics cover over 25 specialties and connect medical expertise with coordinated, family-focused care. Supported by Al-Futtaim Group, the organization is expanding its use of clinical data, digital systems and evidence-based practices to improve healthcare access and outcomes.