Assistant Manager; Data Scientist - AML D&A

As an Assistant Manager (Data Scientist) in the AML domain, you will be responsible for independently executing high-quality Data Analytics, Data Science, and Engineering work. Your role will involve 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 work across various teams and engage with different types of data in cloud-native environments. Strong analytical thinking, hands-on modeling expertise, and adherence to data governance standards are essential for this role. **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. - A 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. The leading financial institution in MENA, with a challenger mindset, is seeking a dynamic Assistant Manager (Data Scientist) for their AML D&A team. Join a diverse and innovative team that puts customers first and pioneers key innovations in banking and financial services. Together, you will help customers find their way to success and contribute to responsible banking practices in the community. As an Assistant Manager (Data Scientist) in the AML domain, you will be responsible for independently executing high-quality Data Analytics, Data Science, and Engineering work. Your role will involve 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 work across various teams and engage with different types of data in cloud-native environments. Strong analytical thinking, hands-on modeling expertise, and adherence to data governance standards are essential for this role. **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 microservi