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Responsible for developing and implementing advanced analytics models to assess credit risk and make data-driven decisions. Develop and maintain predictive models for credit risk assessment using machine learning and statistical techniques. Analyze large datasets to identify trends, patterns, and insights related to credit risk. Collaborate with cross-functional teams to implement risk models into business processes. Lead and mentor a team of data scientists and analysts. Stay abreast of industr

Build dashboards, self-service tools, and reports to analyze and present data associated with business operations and Marketing performance to support key business stakeholders to make data-driven decisions in the organization. Consulting and problem-solving mindset: Ability to work with ambiguity and uncertainty, digest business problems, propose and implement analytical solutions to derive value and outcomes. Support and manage data requests from business stakeholders – can understand business

#About the Team Fazz’s Data Engineering teams are responsible for creating and maintaining the infrastructure that runs the company’s data pipeline, and optimizing the flow and collection of data for the critical business analytics and AI/data-driven solutions. The success of the team relies on the high engineering standard and the adoption of cutting-edge technology that empowers the organization to be agile. Data engineering forms the foundation to ensure that precious data