Healthcare Data Scientist AI Solution Evaluation & Validation
Dubai
About the Role
My client, a leading international healthcare organization, is driving a major AI transformation across global operations. Their Central AI Office is focused on identifying, validating, and integrating the best AI solutions to transform care delivery and operations.
As a Healthcare Data Scientist in the AI Solution Evaluation & Validation team, you'll play a critical role in assessing third-party AI technologies testing performance, robustness, and suitability for real-world healthcare use cases. Instead of building models from scratch, your focus will be on technical due diligence, validation, and impact assessment separating hype from reality to guide strategic AI adoption.
Key Responsibilities
- Conduct rigorous technical assessments of vendor AI solutions, analyzing models, methods, and performance claims.
- Design and execute robust evaluation methodologies and testing protocols for diverse AI applications (predictive, NLP, imaging, etc.).
- Prepare and analyze datasets for validation; run experiments and assess accuracy, bias, and generalizability.
- Develop metrics and statistical tests to evaluate model performance and reliability.
- Interpret and communicate evaluation outcomes clearly for technical and business stakeholders.
- Collaborate with Product, AI Architecture, and Data teams to ensure validated solutions can integrate smoothly into production environments.
- Document methodologies, findings, and recommendations for Go/No-Go decisions.
Qualifications
Essential:
- Master's or PhD in Data Science, Computer Science, Statistics, or a related quantitative field.
- 35+ years of hands-on experience in Data Science or Machine Learning roles.
- Proficiency in Python or R, and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
- Strong grasp of model validation techniques (cross-validation, A/B testing, bias assessment).
- Solid statistical and analytical skills; experience working with large datasets and SQL.
Preferred:
- Experience evaluating third-party AI/ML solutions or MLaaS platforms.
- Background in healthcare or familiarity with medical data (EHR, claims, imaging, genomics).
- Knowledge of ethical AI, fairness, and bias mitigation principles.
- Exposure to cloud ML platforms (AWS SageMaker, Azure ML, Google AI Platform).
- Understanding of data governance, privacy, and compliance frameworks (HIPAA, GDPR)
*** Only successful candidates will be contacted ***
