AI Engineer at Meristem Securities Limited

Job Summary

• To build and deploy the advanced data engineering capabilities that make Meristem's data operationally powerful — including RPA automation, machine learning models, and data intelligence solutions. AI Engineers are responsible for the full cycle from automation design and ML model development through to production deployment and monitoring, delivering measurable business value through intelligent automation and predictive analytics.

Job Details

Machine Learning & AI Engineering

• Design, develop, validate, and deploy machine learning models for commercial and operational use cases including customer segmentation, churn prediction, credit risk, investment analytics, and fraud detection.
• Conduct exploratory data analysis (EDA) to surface patterns, anomalies, and insights within the Group's data assets.
• Build and maintain MLOps pipelines — model versioning, deployment, monitoring, and retraining workflows.
• Monitor deployed models for performance degradation, data drift, and concept drift, retraining as required.

 Robotic Process Automation (RPA)

• Identify, design, build, test, and deploy RPA automation solutions using approved platforms (UiPath, Automation Anywhere, or Power Automate).
• Develop intelligent automation solutions combining RPA with AI/ML capabilities for complex process automation use cases.
• Manage deployed automation bots — monitoring performance, handling exceptions, and conducting lifecycle maintenance.
• Track and report automation value delivered in terms of FTE savings, processing time reduction, and error rate improvements.

Data Intelligence & Analytics Support

• Build and maintain data pipelines and feature engineering processes that support ML models and analytical products.
• Collaborate with the Data Warehouse Manager to ensure clean, reliable data is available for modelling and automation.
• Support the Data Visualization Specialists with advanced analytics outputs and model result visualizations.
• Document all ML models, automation workflows, and data engineering components thoroughly.

Requirements

• Bachelor’s degree from any related discipline
• Master’s degree is a plus
• A minimum of 3-5 years’ experience in Data Science and Analysis.