Join the UAE’s largest bank and one of the world’s largest and safest financial institutions. Our focus is to create value for our employees, customers, shareholders and communities to grow through differentiation, agility and innovation. We are looking for top talent and your success is our success. Accelerate your growth as you help us reach our goals and advance your career. Be ready to make your mark a top company, in an exciting & dynamic industry. 

Job Purpose

An experienced Senior Manager in Data Science with a strong background in banking and expertise in MLOps. This role involves leading a team to leverage data science in the banking sector, including risk management, fraud detection, and customer analytics. Key responsibilities include banking expertise, MLOps leadership, team management, model deployment, CI/CD, monitoring, collaboration, compliance, and documentation.

Key Accountabilities

1. Banking Expertise:

• Leverage your in-depth knowledge of banking processes, risk management, fraud detection, customer analytics, and other relevant areas to develop data science strategies that address industry-specific challenges.

1. MLOps Leadership:

• Develop and execute an MLOps strategy, ensuring efficient deployment of machine learning models in a banking context while maintaining performance, security, and compliance.

1. Team Management:

• Lead, mentor, and manage a team of data scientists and engineers, fostering collaboration and skill development within the team.

1. Model Deployment:

• Oversee the deployment of machine learning models into production environments, ensuring high availability, scalability, and adherence to regulatory standards.  Continuous Integration and Delivery (CI/CD): Establish and manage CI/CD pipelines for machine learning workflows to automate testing, validation, and model updates in a banking environment.

1. Monitoring and Optimization:

• Implement monitoring solutions to track model performance, system health, and resource usage, proactively optimizing models and processes.

1. Collaboration:

• Collaborate with cross-functional teams, including banking experts, data engineers, software developers, and business stakeholders to align data science and MLOps initiatives with overall business goals.

1. Compliance and Security:

• Ensure that all data science and MLOps processes adhere to banking regulations, data privacy standards, and company policies.

1. Documentation:

• Maintain comprehensive documentation of MLOps processes, data science workflows, and model versions.

1. Industry Knowledge:

• Stay current with industry trends and emerging technologies in banking, data science, and MLOps to ensure our organization remains competitive.

• Bachelor's or Master's degree in a related field (e.g., Data Science, Finance, Computer Science).
• Proven experience in managing and leading data science teams in a banking context.
• Strong knowledge of MLOps tools and practices.
• Proficiency in programming languages such as Python and relevant data science libraries.
• Familiarity with banking regulations and compliance.
• Excellent problem-solving and communication skills. –

• Strong project management skills and ability to meet tight deadlines

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