• 1.1 Data Management and Engineering Support • Contribute to structuring, cleaning, validating, and optimizing Tugende’s enterprise data in the Redshift-based Data Warehouse. • Develop and maintain reusable SQL queries and data pipelines to support analytics and reporting needs. • 1.2 Reporting and Dashboard Development • Build and update interactive Power BI dashboards to monitor operational, financial, and credit KPIs. • Automate and publish reports for month-end performance, credit risk, recovery operations, and marketing KPIs. • 1.3 Machine Learning & Model Development • Support the development of models for: • Credit scoring and provisioning. • Fraud detection and revenue leakage prevention. • Asset repossession prediction and asset financing behavior modeling. • GPS geostatistics for asset tracking and client safety. • Participate in deploying ML pipelines using: • Containerization tools like Docker for packaging and deployment. • MLFlow (or similar tools) for versioning and performance monitoring. • AWS services (e.g., EC2, Lambda, S3, CloudWatch) under senior team guidance. • Ensure models are monitored and versioned for continuous improvement. • 1.4 Operations Research & Optimization • Assist in developing optimization models to: • Allocate assets and staff across branches. • Plan vehicle/asset maintenance and rotation. • Optimize cost-performance trade-offs in recovery and servicing. • Perform portfolio, revenue, and risk projection stress testing. • Use optimization tools/libraries (e.g., Pyomo, SciPy, PuLP) based on problem complexity. • 1.5 Generative AI & Automation Initiatives • Support implementation of AI Agents for: • Underwriting and risk assessment. • Plate detection/image validation for vehicles and bikes. • Internal knowledge base querying (LLM-powered policy agents). • Chatbots for client servicing and operations support. • Assist senior engineers in model monitoring and maintenance. • 1.6 Documentation & Collaboration • Document models, pipelines, and tools using clear technical documentation standards. • Collaborate with business teams to understand pain points and deliver tailored data solutions. • Prepare and deliver presentations/reports to senior leadership using PowerPoint, dashboards, or interactive notebooks. • Participate in internal data literacy initiatives to empower end users across departments.

• 1.1 Data Management and Engineering Support • Contribute to structuring, cleaning, validating, and optimizing Tugende’s enterprise data in the Redshift-based Data Warehouse. • Develop and maintain reusable SQL queries and data pipelines to support analytics and reporting needs. • 1.2 Reporting and Dashboard Development • Build and update interactive Power BI dashboards to monitor operational, financial, and credit KPIs. • Automate and publish reports for month-end performance, credit risk, recovery operations, and marketing KPIs. • 1.3 Machine Learning & Model Development • Support the development of models for: • Credit scoring and provisioning. • Fraud detection and revenue leakage prevention. • Asset repossession prediction and asset financing behavior modeling. • GPS geostatistics for asset tracking and client safety. • Participate in deploying ML pipelines using: • Containerization tools like Docker for packaging and deployment. • MLFlow (or similar tools) for versioning and performance monitoring. • AWS services (e.g., EC2, Lambda, S3, CloudWatch) under senior team guidance. • Ensure models are monitored and versioned for continuous improvement. • 1.4 Operations Research & Optimization • Assist in developing optimization models to: • Allocate assets and staff across branches. • Plan vehicle/asset maintenance and rotation. • Optimize cost-performance trade-offs in recovery and servicing. • Perform portfolio, revenue, and risk projection stress testing. • Use optimization tools/libraries (e.g., Pyomo, SciPy, PuLP) based on problem complexity. • 1.5 Generative AI & Automation Initiatives • Support implementation of AI Agents for: • Underwriting and risk assessment. • Plate detection/image validation for vehicles and bikes. • Internal knowledge base querying (LLM-powered policy agents). • Chatbots for client servicing and operations support. • Assist senior engineers in model monitoring and maintenance. • 1.6 Documentation & Collaboration • Document models, pipelines, and tools using clear technical documentation standards. • Collaborate with business teams to understand pain points and deliver tailored data solutions. • Prepare and deliver presentations/reports to senior leadership using PowerPoint, dashboards, or interactive notebooks. • Participate in internal data literacy initiatives to empower end users across departments.