using sophisticated analytics and Machine Learning models to address difficult business challenges and generate strategies, build models, and embed those models into software-driven business processes. The successful Feature Engineering, and Model Evaluation. DUTIES: Data Analysis and Modeling – Develop and deploy Machine Intelligence models and algorithms to extract insights, predict outcomes, and optimize processes. Conduct data for modeling. Work with Data Engineering teams to ensure data availability and quality. Model Evaluation
infrastructure and systems that enable efficient data processing, storage, and retrieval. You will also help ensure or Informatica. DUTIES: Data Architecture and Modeling - Design and develop data architectures that support organization's data needs. Design and optimize data models to ensure efficient data storage, retrieval, and Development and Maintenance - Develop and maintain ETL processes to extract, transform, and load data from various troubleshoot ETL processes to ensure timely and accurate data processing. Optimize ETL processes for performance
support high performing ML algorithms, predictive models and support real-time data visualisation requirements must be adept at design and development of ETL processes. SQL development experience, preferably SAS data methodology. Adept at design and development of ETL processes. SQL development experience, preferably SAS data methodology. Knowledge of retail industry data models. Advanced knowledge of compliance and IT governance Stakeholder Management. Data Architecture, Data Modelling and Data Pipelining. Solutions Architecture. ATTRIBUTES:
remote role that includes data manipulation, modelling and being responsible for the understanding of inter-dependencies between various data sources and business processes involving data flow. You will also be involved You must have experience with Data Analysis, modelling, surfacing, Data Cleaning/Integrity Checking and clients, the focus being the research and investment process of these Asset Managers. Construct end to end data architectures (such as databases and large-scale processing systems). Ensure data architecture will support
improving operational efficiency, optimizing business processes, and enhancing overall performance. The ideal teams to support data-driven decision-making processes. Provide analytical support for business initiatives performance tracking. Identify opportunities for process improvement, operational efficiencies, and revenue knowledge of statistical analysis techniques, data modelling, and data visualization tools. Participate in with Statistical Analysis techniques and Data Modelling. Proficiency in Microsoft Excel and other data
Create system design documents, including data models, flowcharts, and interface designs. Work closely Continuous Improvement - Identify opportunities for process improvements and optimization in the Software Development methodologies and best practices. Proficiency in system modeling tools and techniques. Must be willing to travel
and Data Science teams to develop and deploy AI models that improve debt collection strategies and customer platforms. Manage Data Warehousing solutions and ETL processes, optimizing data storage and retrieval. Collaborate background in Data Warehousing, SQL, and ETL processes. Experience with AI and Machine Learning technologies Advantageous – A solid understanding of Contact Center processes and technology. Experience with Cloud-based BI
data collection, data cleaning and manipulation, model creation, analysis, and presentation of clients
that it can be translated into a specific data model. Further refining the physical design to meet system Operations - Suggest areas for improvement in internal processes along with possible solutions. Lead internal teams/task
beneficial. Experience working with databases and data models beneficial. Qualifications: Matric certificate