Top Data Jobs in Singapore

Design, build, and optimize scalable infrastructure to support large-scale training and inference of generative AI models. Improve platform performance, cost efficiency, observability, and operational controls while collaborating with engineering, analytics, and product teams to deliver robust AI solutions.

Support design, build, and maintenance of infrastructure for large-scale training and inference of generative AI models. Develop and optimize data pipelines, implement AI application infrastructure, recommend technologies, add operational controls and governance, build observability for platform reliability, and collaborate with cross-functional teams while exploring emerging data engineering practices.

Sustain and operate Marvell's Silicon.da test data analytics platform: monitor and resolve data loading and quality issues, support users via ServiceNow/Slack, coordinate with vendors and foundries, maintain documentation, and drive issue closure and operational readiness.

The Data Scientist role involves designing experiments, analyzing model performance, and integrating ML features while collaborating in an Agile environment.

The Senior Reliability Engineer for Mechanical Systems oversees the health of cooling systems, ensuring their operational efficiency through maintenance planning, technical support, and root cause analysis. They work with design and construction teams, providing feedback and training to enhance system reliability and support operational teams in critical situations.

Lead enterprise data strategy, architecture, governance, and delivery. Design scalable data platforms, pipelines, and analytics solutions; enforce data quality, MDM, and metadata standards. Advise senior stakeholders, lead cross-functional teams, and manage end-to-end delivery to meet timelines, KPIs, and business value.

Lead Enterprise AI initiatives by designing, developing, and deploying AI/GenAI solutions. Partner with data engineers, technologists and business stakeholders to prototype, integrate, validate and benchmark LLM and advanced-model applications, manage expectations, and translate analytic results into business outcomes.

Lead regional go-to-market strategy and execution for complex product portfolios. Translate client needs into product requirements, manage product launches and marketing lifecycle, drive commercial success, and lead cross-functional teams and sales managers to achieve revenue, customer retention, and strategic objectives.

Lead pre-sales technical design and architecture for Agentforce and Data Cloud (D360). Design integrations with external agents and hyperscalers, build prototypes and demos, define prompt engineering and agent lifecycle best practices, advise on data modeling and ingestion patterns, and provide technical enablement and documentation to internal teams and customers.

Support deployment of marketing analytics for Consumer Banking by performing data discovery, building and maintaining predictive models, campaign reporting, segmentation, and campaign execution support. Collaborate with product managers, data engineers, and data scientists to improve marketing effectiveness, automate campaign processes, and translate data into actionable insights for customer acquisition, cross-sell and activation.

The role involves leading BIO initiatives, collaborating with sales teams, enabling digital capabilities, and engaging stakeholders to enhance agent productivity and business outcomes.

The Operations Analyst oversees market data management, ensuring accuracy, conducting analysis, and improving operational processes for business divisions in Singapore.

The Control and Metrics External Data Analyst will manage external data usage, oversee external data initiatives, and support the Chief Data Officer in implementing the Bank's data strategy.

As a Data Scientist, you'll develop predictive models, analyze large datasets, and collaborate with stakeholders to drive data-informed business decisions.

Lead the development and delivery of reporting and analytics platforms, optimizing marketing campaigns, advising on MarTech solutions, and driving digital maturity for clients.

Conduct data analysis using SQL and Python, automate processes, collaborate with teams, and assist with UAT migration tasks.

The Senior Data Scientist will deliver analytics solutions, develop scalable data products, and work on machine learning and statistical models to solve operational challenges.

The intern will design safe processes, analyze behavior for anomalies, track fraudulent accounts, and maintain machine learning models to enhance account safety.

The role involves resolving client solution requirements, managing installations and troubleshooting issues across multiple technologies, focusing on collaboration and networking solutions.

The Technical Services Systems Integration Specialist provides technical support, engages with clients, escalates issues, and mentors junior engineers while focusing on technical implementations across multiple technologies.

As a Global Client Manager, you will build and manage client relationships, ensuring satisfaction and driving sales growth using strategic planning and Salesforce tools.

Manage data provisioning and enablement by collaborating with business units to provision datasets into playpens, maintain workflows, ensure governance and secure data movement, monitor usage, onboard users, document lineage/configurations, troubleshoot access issues, and foster stakeholder relationships to support self-service data exploration and analytics.

The Data Engineer is responsible for designing and maintaining scalable data systems, building data pipelines, and collaborating with teams to support analytics and AI use cases.

Develop and deploy AI/ML and generative-AI solutions: collaborate with stakeholders, research methods, perform data wrangling and feature engineering, maintain deployed models/assistants, build backend APIs and frontend interfaces, document products and fix security issues.

Design, build, and maintain large-scale batch and real-time data pipelines, ETL/ELT processes, and data stores (data lakes, marts, warehouses). Perform data extraction/cleaning (including web scraping), integrate data silos, develop backend APIs, and collaborate with cross-functional teams in an Agile CI/CD environment.