Healthcare Data Scientist - Machine Learning & Clinical Analytics

🏢 Al Futtaim Private Company (LLC)
📍 United Arab EmiratesFull-timeOn-site
📅 Posted: 2w ago🔄 Updated: 2w ago
CV%
✨ AI Summary
This role involves building, training, and evaluating predictive machine learning models for various healthcare use cases, including risk prediction, patient outcomes, and revenue cycle optimization. The Data Scientist will analyze diverse healthcare datasets (EHR, clinical, claims, etc.) using advanced SQL and statistical/machine learning techniques. Responsibilities include preparing analytical datasets, working with healthcare data standards, collaborating with clinicians, evaluating model performance, and ensuring data privacy and ethical AI use. Required qualifications include a Bachelor's degree in a quantitative field, 2-5 years of data science experience, and at least 2 years in healthcare data. Strong Python/R and SQL skills are necessary, along with an understanding of healthcare coding and interoperability standards. Excellent communication skills are vital for translating technical findings to stakeholders. A Master's or PhD, experience with UAE healthcare data, and familiarity with model explainability and visualization tools are highly desirable. 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, s
Required Skills
Information Technology
○Predictive Modeling○Data Extraction○Machine Learning○Clustering○XGBoost○SQL○Python○Data Science
Other
○clinical analytics○healthcare data○classification○random forest○R○ICD-10○ICD-11○CPT○SNOMED CT○LOINC○HL7○FHIR○Senior Clinical Analyst○Medical Data Analyst
Operations, Logistics & Supply Chain
○Logistics
Science & Research
○Risk & Survival Analysis
Soft Skills & Professional Competencies
○Communication
Nice to have:
Other
○SHAP○LIME○model explainability○Plotly
Information Technology
○Power BI○Tableau○Dashboards
Requirements

  • 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.

Description
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.
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🎯 Overalli74%
⚡ Skillsi85%
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Ontology Match: 85.0
Matched:✓ Requirements Matching✓ Ontology Skills Mapping
📜 Eligibilityi49%
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Local: 19600%
🏗️ Career Fiti91%
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Seniority: 91.0
📋 Requirementsi67%
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Domain: 67.0
🔥 Motivationi78%
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Title Fit: 78.00