Top Data Jobs in Singapore

The Staff Data Scientist will design experiments, improve payment products, build measurement frameworks, and mentor junior data scientists at Airwallex.

The Data Scientist will analyze extensive data using advanced techniques in machine learning and optimization to derive insights and create predictive models.

The role involves managing AI system reviews, conducting risk assessments, ensuring compliance, and collaborating with teams to enhance AI governance and reporting processes.

As a Data Science Engineer, you will analyze large datasets, develop predictive models, and work collaboratively to enhance data tools and processes.

Lead Prudential's AI Lab, driving development of AI solutions, managing sandbox operations, overseeing product quality, mentoring teams, and engaging with external AI talent.

The intern will manage data in an e-catalogue focusing on vehicle data, conduct business analysis using Power BI, and assist with customer support and process improvements.

The Associate Graduate will participate in an immersive program to gain hands-on exposure to modern technologies, work on client projects, and develop industry-recognized certifications. Responsibilities include learning about cloud computing, data engineering, AI/ML, and collaborating with experienced professionals.

Lead Kubernetes migration initiatives to Azure Kubernetes Service, manage container modernization, CI/CD integration, and provide advanced technical support and operational governance. Engage with stakeholders and mentor engineers to ensure project success and operational readiness.

The Kubernetes Migration Engineer executes the migration and deployment of workloads to Azure Kubernetes Service, supporting configuration, monitoring, troubleshooting, and ensuring operational stability.

The Application Technical Lead is responsible for leading application discovery, migration planning, and providing technical governance for enterprise infrastructure transformation, with a focus on Azure IaaS and hybrid cloud solutions.

Lead end-to-end Virtual Machine migration from on-premise to Azure. Ensure cohesive delivery covering assessment, execution, and stabilization. Provide advanced technical support for complex escalations and drive operational excellence in cloud environments.

The Cloud Engineer executes the migration of on-premise virtual machines to Azure, ensures operational stability, troubleshoots issues, and adheres to ITIL processes.

The Database Engineer manages database migration to Azure, supports SQL Server and MySQL operations, ensures performance and security, and troubleshoots issues within SLAs.

The Data Engineer 2 will design, develop, and maintain data pipelines, frameworks, and models, ensuring data quality and governance while collaborating with scientists and analysts.

The Senior System Engineer will perform operational tasks, provide support for escalated incidents, implement automation, and manage technology projects.

As a Senior Client Manager, you will manage and grow client relationships, drive expansion, and ensure satisfaction throughout the client lifecycle. You'll leverage sales tools, develop effective communications, and contribute to revenue growth while coordinating internal and external resources for sales opportunities.

The DevOps Engineer is responsible for designing, implementing, and maintaining software solutions based on business requirements, utilizing multi-technology applications and CI/CD processes.

As a Sales Executive Lead, you will drive off-cycle growth by upselling live data services, managing accounts, and collaborating with teams to build a robust sales pipeline.

The Vice President of Investment will evaluate investment opportunities, structure transactions, manage due diligence, and collaborate with advisors while supporting asset management initiatives.

Manage HR data engineering initiatives by building data warehouses and pipelines. Transition to analytics, generating reports and dashboards for informed HR decision-making.

The Executive in CRM, Data Analytics & Customer Experience supports customer engagement initiatives through managing CRM programs, customer feedback, and performance analytics to enhance satisfaction and loyalty.

Lead a rapid‑response PMO to drive enterprise transformation across AI, data analytics, digital assets and platform initiatives. Diagnose complex cross‑domain problems, prototype and scale production solutions, institutionalise reusable architectures and governance, manage partners, and align stakeholders to accelerate secure, compliant, and enterprise‑grade innovation.

Lead the development and deployment of Generative AI applications, collaborate with teams to deliver business use cases, and enhance data science skills.

The Data Scientist will identify new data sets, build processes for data collection, analyze data for potential applications, and research alpha signals for portfolio managers.

Lead a unified data and experimentation framework across the company, engaging with core business lines to support data-driven decision-making, while ensuring data quality and governance.