Junior Data Scientist (Emiratisation)

**Role Purpose:** Support delivery of ML \+ GenAI (LLM) use cases in a regulated banking environment, with primary focus on model documentation, AI governance, and Model Risk Management (MRM) readiness. **Key Responsibilities:** * Work with large and complex data sets to solve challenging business problems * Support development and controlled updates of ML/GenAI components mainly to ensure reproducibility, versioning, and governed release. * Document evaluation results for ML/LLM components (test cases, thresholds, failure modes, mitigations) to enable governance review and validation readiness. * Produce and maintain audit\-ready model documentation (purpose, scope, data lineage/governance, methodology, assumptions, limitations, evaluation evidence, monitoring plan, change log). * Support MRM governance deliverables: Model Charter inputs, Model Inventory updates, and AI risk assessment/tiering evidence packs (including Human\-in\-the\-Loop aspects where required). * Document evaluation results for ML/LLM components (test cases, thresholds, failure modes, mitigations) to enable governance review and validation readiness. **Professional Experience/Qualifications:** * Experience: 0\-3 years (Data Science AI/ML; banking preferred) * Python (pandas/NumPy/scikit\-learn) and SQL; strong data preparation \+ EDA foundations. * Solid understanding of ML fundamentals and model evaluation concepts. * Working knowledge of GenAI/LLM basics (prompting/RAG concepts) and ability to document risks/controls clearly. * Demonstrated exposure to model documentation / governance / MRM in a regulated or enterprise setting (charter, inventory, risk assessment, monitoring documentation). * Strong written communication: ability to turn technical work into crisp, structured documentation * Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g., Sagemaker, Vertex AI) * Educational qualifications: Bachelor’s degree in computer science, Engineering, Data Science / Statistics or related field.