Integrate data from multiple sources into centralised platforms for analytics and reporting, including API integration with internal and external applications and Kafka for real-time streaming
Data Preparation: Cleaning and preprocessing data to make it suitable for analysis, implementing data transformation processes to extract data for the creation and loading of Data Products. Provide strategic recommendations that enhance productivity and business performance
Experience working with complex, large-scale datasets, including assessing data quality, tracing data lineage, investigating anomalies and documenting analytical assumptions.
Hands-on experience developing, validating or enhancing predictive, risk-scoring, fraud-detection or anomaly-detection models, including feature development, back-testing, threshold calibration and performance evaluation using measures such as precision, recall and related trade-offs.
Data Governance & Quality: Implement data quality monitoring frameworks, enforce privacy compliance (PDPA), and maintain data lifecycle policies including retention and archiving.
Develop, deploy and act as the single point of contact for specific data science problems within Maintenance domain, technology support, uptake and value generation.
Business Discovery & Analysis: Engage clients to understand business challenges, map workflows and customer journeys, and identify opportunities for AI/ML implementation.