Top Tech Jobs & Startup Jobs in Singapore

The VP, Infrastructure Engineer will build and support a secure IT infrastructure, manage systems, and enhance processes while ensuring compliance with regulatory standards.

You will oversee branches and GCD departments, focusing on risk controls, AML, fraud handling, and using data analytics to manage risks. Drive initiatives to enhance risk culture and support compliance through testing and reviews.

Use large datasets to produce dashboards, reports and visualizations; identify trends and anomalies; perform statistical analysis and predictive modeling; collaborate with business units to translate needs into specifications and resolve data quality issues; communicate findings to non-technical stakeholders.

Lead Plan & Change teams in IT infrastructure operations, ensuring efficiency and regulatory compliance while driving innovation and strategic management across ASEAN and North Asia.

The VP, eFX Developer will develop a modern FX Algo E-Trading system in Java, ensuring low-latency performance, and collaborate with cross-functional teams.

Lead strategies for acquiring wealth customers, manage product features, oversee digital launches and ensure compliance in the financial sector.

The role involves managing regulatory reporting related to capital positions, supporting submissions to regulators, developing dashboards, and enhancing processes. Requires strong experience in banking and finance.

Lead strategy and transformation initiatives across the bank: develop strategic viewpoints and papers, support program delivery with business stakeholders, participate in management committees, track actions, and contribute to team development and recruitment.

Lead cost optimization and financial analysis, develop financial models, monitor costs, and provide strategic insights for property-related projects within UOB's Group Corporate Real Estate Services.

Lead development and delivery of AI/ML analytics for integrated surveillance across AML, sanctions, fraud and scams. Define data science strategy, build detection models and reusable risk features, ensure model governance and explainability, partner with data engineering and compliance stakeholders, drive production deployment and adoption, and mentor analytics teams to address emerging financial crime risks.