the business intelligence framework, driving operational optimisation and data-driven decision-making SQL, and ETL processes. Experience with AI and machine learning technologies and their application in
solutions for healthcare analytics. • Implement machine learning models to improve risk assessment and statistical software, programming languages and machine learning applications (e.g., R, Python), and data
solutions for healthcare analytics. • Implement machine learning models to improve risk assessment and statistical software, programming languages and machine learning applications (e.g., R, Python), and data
infrastructure of the bank to enable advanced analytics, machine learning and artificial intelligence by providing pipelines run successfully. Operations: Support and run daily operational reports to ensure that all jobs
Engineer with the capabilities of utilising data, machine learning, statistical and mathematical models to
GIT, Artifactory, Redmine, Working in Virtual Machines. Social Competencies: Positive thinking. Excellent
required to build both predictive and prescriptive machine learning models that will assist with increasing
Change Agility, Credit Risk Analysis, Data Science, Machine Learning, Predictive Modelling, Problem Solving
and is compatible with browsers, devices, or operating systems; and Recommend and implement performance communication protocols, programming languages, and operating systems software and hardware. • Test: Develop Document test plans, procedures, or results. • Operate: Perform application support on rotational basis; component driven applications • Concepts SOLID State machines Development Tools Azure Dev Ops GIT Scheduling
& Maintenance: Creating and setting up virtual machines with VMWare VSphere/esxi Proactive Windows and