Assistant Manager (Data Scientist)

As an Assistant Manager (Data Scientist) at this leading financial institution in MENA, you will play a crucial role in independently executing high-quality Data Analytics, Data Science, and Engineering work within the AML domain. Your responsibilities will include designing and developing machine learning, deep learning, graph analytics, and LLM/RAG-based solutions to enhance AML detection, behavioral insights, and investigative intelligence. You will be transforming complex datasets into clear, actionable insights and contributing to building production-ready analytical assets that support AML operational and business decisions. Key Responsibilities: - Lead and execute data-driven initiatives within the AML domain, working independently on projects with minimal guidance. - Design and develop advanced machine learning, deep learning, and graph analytics models to strengthen AML detection and behavioral intelligence. - Build and deploy LLM/RAG-based analytical tools, investigative copilots, and knowledge retrieval systems to enhance investigative capabilities. - Perform in-depth behavioral analytics, network analysis, and typology detection to support AML operations and decision-making. - Create reusable analytical assets and insights for AML stakeholders, utilizing dashboards and structured summaries for effective communication. - Collaborate with engineering teams to implement reliable ML/LLM pipelines, ensuring seamless CI/CD workflows and monitoring. - Integrate analytical components with downstream systems through APIs and microservice interfaces for efficient data flow. - Apply robust data governance principles, ensuring data quality, metadata management, and access controls across enterprise-wide data. - Prepare and maintain MRM-compliant documentation, validation packs, and monitoring frameworks to ensure model compliance and effectiveness. Qualifications Required: - A bachelor's degree in Computer Science, Data Science, or a related field is required. - Minimum of 5 years of experience in a similar role, with a strong background in AML compliance and data analytics. - Proven expertise in developing advanced machine learning, deep learning, and graph analytics models for AML use cases. - Experience with LLM/RAG technologies and their application in investigative and knowledge-retrieval systems is essential. - In-depth knowledge of AML regulations, including CBUAE guidelines and internal governance frameworks. - Excellent collaboration and communication skills, with the ability to work effectively across diverse teams. - Proficiency in data engineering and management, including data structures, feature stores, and analytical datasets. - Familiarity with cloud-native platforms and their role in handling enterprise-wide structured, semi-structured, and unstructured data. - Analytical mindset with a problem-solving approach and a passion for driving data-driven initiatives and innovation. - Ability to work independently, manage projects, and ensure compliance with regulatory standards and expectations. This dynamic role offers you the opportunity to apply advanced ML/GenAI techniques in a real-world financial-crime context and grow into a full-stack data science leader. Join us in pioneering key innovations and developments in banking and financial services, while actively contributing to the community through responsible banking. As an Assistant Manager (Data Scientist) at this leading financial institution in MENA, you will play a crucial role in independently executing high-quality Data Analytics, Data Science, and Engineering work within the AML domain. Your responsibilities will include designing and developing machine learning, deep learning, graph analytics, and LLM/RAG-based solutions to enhance AML detection, behavioral insights, and investigative intelligence. You will be transforming complex datasets into clear, actionable insights and contributing to building production-ready analytical assets that support AML operational and business decisions. Key Responsibilities: - Lead and execute data-driven initiatives within the AML domain, working independently on projects with minimal guidance. - Design and develop advanced machine learning, deep learning, and graph analytics models to strengthen AML detection and behavioral intelligence. - Build and deploy LLM/RAG-based analytical tools, investigative copilots, and knowledge retrieval systems to enhance investigative capabilities. - Perform in-depth behavioral analytics, network analysis, and typology detection to support AML operations and decision-making. - Create reusable analytical assets and insights for AML stakeholders, utilizing dashboards and structured summaries for effective communication. - Collaborate with engineering teams to implement reliable ML/LLM pipelines, ensuring seamless CI/CD workflows and monitoring. - Integrate analytical components with downstream systems through APIs and microservice interfaces for effic