Lead- Machine Learning Ops

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. 

Key Accountabilities

• Enabling Engineering/Transforming capabilities to support ML, Build tool Supported or business needed custom transformations to perform data preparation and make it ready for ML, Enable End to End MLOps framework, Automated pipelines, containerization, templatization, CI/CD, etc.
• The role requires job holder to be a creative thinker and able to propose innovative ways to look at business problems by using data mining (the process of discovering new patterns from large datasets) approaches on the set of Information available. They will need to validate their findings using an experimental and iterative approach. Also, Data Scientist will need to be able to present back their findings to the business by exposing their assumptions and validation work in a way that can be easily understood by their business counterparts.
• Datasets in the Analytical tool to be promoted into the Feature Store, showing both data quality and trustworthiness, and can assist with simplifying re-use. Users can access feature store to reuse cleaned/reference datasets in their projects.
• To Enable data quality with an automatic meaning detection algorithm (With in the FAB selected Analytical tool of choice) and support using the 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 in the column. The user can drill deeper to view a detailed histogram, summary statistics, and the ability to drop invalid rows with just a few clicks. Automatically sorted visual data quality assessments and statistical summaries on categorical and numerical data. Machine learning based visual assessment of values clustering. Automatically detect and handle unique and invalid values and outliers and a Wizard for anomaly detection.

• 5+ Years of Experience in AL ML Tooling and ML Ops Practice Setup
• Solid hands on Modelling tools Like DataIKU, SAS Viya or had already used Azure ML OPS.
• Terraform experience, Python Coding Required.
• Candidate must possess at least a Graduate or bachelor’s degree in Computer Science/Information Technology, Engineering (Computer/Telecommunication) or equivalent.
• Good to be certified in Model Ops, ML Ops.
• DataIKU
• SAS (Base SAS,EMiner ,EG)
• Statistical modelling, Machine Learning and AI(Pattern recognition, Natural language processing, computer vision)
• Data Visualization (Power BI)
• Data modelling: json, xml
• Deep learning technologies (Neural networks, LSTM, GAN,RNN,etc..)
• Deep learning frameworks(Tensorflow/pytorch/Maxnet)
• Cloud deployment: Google cloud platform/amazon/Microsoft azure
• Experience in drafting solution architecture frameworks that rely on API’s and microservice
• Expertise in distributed computing environments / big data platforms (Cloudera, Hadoop, Apache spark,Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.)

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