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Sub Division: Data Analytics and Artificial IntelligenceDivision: GCOOCompany DescriptionJoin 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 at a top company, in an exciting & dynamic industry.Job DescriptionJob PurposeBuilding/Enabling Model Deployment framework across FAB Analytics, enabling a feature bank or feature store, and enhancing capabilities to select the best algorithms or UI to play with.Key AccountabilitiesCreate and support monitoring tools to understand users and activities running on the server, providing a platform for more granular monitoring services.Support Model Monitoring with native features for detecting model drift and data drift.Build a powerful automated machine learning engine that allows for highly optimized models with minimal intervention, having full control over all training settings, algorithm settings, and the optimization process, including the ability to write custom models and use advanced deep learning models.Promote datasets in the Analytical tool into the Feature Store, ensuring data quality and trustworthiness, assisting with simplifying re-use. Users can access the feature store to reuse cleaned/reference datasets in their projects.Enable data quality with an automatic meaning detection algorithm (within the FAB selected Analytical tool of choice) and support using built-in/custom developed visual tools for establishing data quality. For example, each column includes a simple histogram to show the number of valid records, with the ability to drill deeper for detailed histograms, summary statistics, and the option to drop invalid rows easily.Qualifications5+ years of experience in AL ML tooling and ML Ops practice setup.Solid hands-on experience with modeling tools like DataIKU, SAS Viya, or Azure ML Ops.Experience with Terraform and Python coding is required.Candidate must possess at least a graduate or bachelor's degree in Computer Science/Information Technology, Engineering (Computer/Telecommunication), or equivalent.Certification in Model Ops or ML Ops is preferred.Additional certifications in Machine Learning, Artificial Intelligence, and scripting languages such as Spark, Python, SQL, Scala, and others are advantageous.Certifications in various cloud environments are an added advantage.
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