Top Data Jobs in Singapore

Manage, maintain, and optimize critical database systems (SQL Server, Oracle). Perform installs, patches, backups, access control, monitoring, performance tuning, incident/change/problem management, on-call support, capacity planning, automation, reporting, and collaborate with global teams and site stakeholders.

Analyze semiconductor manufacturing data to identify yield detractors, build data pipelines, apply statistical and machine learning models for yield improvement, support DOE experiments, and create automated dashboards and reports for engineering stakeholders.

The role involves developing technology policies, conducting research, coordinating AI efforts, and engaging with stakeholders to strengthen Singapore's digital economy.

The Technical Product Manager is responsible for product outcomes across the lifecycle, involving product vision, stakeholder engagement, backlog prioritization, and technical leadership.

The Transformation Lead for AI in APAC will manage change and drive adoption of AI tools across the studios, engage stakeholders, and run training programs.

The Enterprise BD Manager will expand and maintain key enterprise accounts, driving growth through strategic relationships and complex solution structures in maritime risk and sustainability.

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

The AI Architect will develop AI solutions, support the global AI sandbox, provide technical guidance, and optimize AI products while collaborating with various stakeholders.

The Staff Data Scientist will optimize semiconductor manufacturing processes through data analysis, statistical modeling, and data visualization, collaborating closely with engineering teams.

Design, build, and ship agentic AI applications that answer business questions over governed data. Implement RAG, NL-to-query, tool/function calling, and evaluation/guardrails. Partner with data teams on metrics, models, pipelines, and apply strong data governance and security for financial services.

Develop and deploy optimization, simulation, and ML models to improve semiconductor factory capacity, throughput, and cycle time. Partner with cross-functional manufacturing and engineering teams to analyze constraints, run scenario analyses, and deliver data-driven recommendations integrated into production pipelines and decision-support tools.

Lead design and deployment of agentic AI for manufacturing planning and operations. Build multi-agent systems combining LLM reasoning and optimization (MIP, heuristics, simulation), integrate agents with data pipelines and enterprise systems, and deliver solutions for capacity planning, production flow optimization, and decision automation. Partner with planning, operations, data engineering, and MLOps teams to translate domain requirements into deployable AI workflows and reusable orchestration frameworks.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Maintain, design, and enhance the Group AI and model inventory system to support AI governance. Implement process improvements, integrate automation, collaborate with model owners, risk, compliance, IT and external reviewers, and drive future-state system implementation and regulatory compliance for Generative and Agentic AI models.

Manage cost planning, procurement, contract administration, cost control and reporting for large-scale data centre and mission-critical projects. Lead tendering, evaluate contractors, manage variations and claims, support value engineering, risk management, stakeholder coordination and financial close-out across CSA or MEP trade packages.

Manage cost planning, procurement, contract administration, cost control and reporting for large-scale data centre/mission-critical projects. Produce estimates, budgets, tender evaluations, manage variations and claims, support value engineering, stakeholder coordination, risk management and project close-out.

Lead planning and delivery of construction/data centre fit-out projects: manage programmes, schedules, procurement, site coordination, stakeholder engagement, reporting, team development, compliance, quality, safety and budgets.

Support cost management for Civil, Structural & Architectural works on a large data centre. Assist with cost estimating, tendering, procurement, change management, cost reporting, contractor claims review, stakeholder coordination, and governance to ensure cost control and accurate financial reporting throughout the project lifecycle.

Manage and maintain all project documentation for large-scale data centre construction: control drawings, RFIs, submittals, approvals, QA/QC, commissioning and handover records. Administer document management systems (ACC), track workflows, coordinate stakeholders, compile O&M manuals and support audits to ensure compliance with project and client procedures.

Lead planning and delivery of commercial fit-out and data centre projects, managing schedules, budgets, change control, governance, safety compliance, stakeholder engagement, and cross-functional teams. Prepare progress reports, capture lessons learned, and identify business development opportunities.

Design and build scalable, metadata-driven data pipelines, frameworks and services for AI/ML use cases. Lead end-to-end SDLC, deliver high-quality backend solutions, manage production support and CI/CD, collaborate with stakeholders, perform POCs, and drive process improvements and automation.

Participate in a 3–6 month accelerator as a Data Product Manager focusing on trading insights. Analyze trading and user data, propose and deliver product enhancements, collaborate cross-functionally, monitor product performance, gather feedback, and manage end-to-end product lifecycle to improve engagement and conversion.

Lead techno-functional data solutions for Wholesale Banking, Retail, and Global Markets. Gather requirements, design/validate data models (Teradata FSDM, dimensional), profile and map data from core systems, author specifications, collaborate with architects and engineers, execute data validation tests, and provide data-driven insights for strategic decisions.

Design and build enterprise-scale ingestion frameworks and Lakehouse platforms. Develop reusable Spark/Python components, data models, data products, quality controls, and observability. Support CI/CD, DevOps, Kubernetes-based deployments, and operationalize ML models for AI-driven analytics and risk/fraud use cases in banking.

Develop and maintain Python libraries, services, and frameworks for data pipelines used in trading and research. Collaborate with quantitative and tech teams to design data models, deploy resilient data platform tooling, improve development velocity, write design/requirements docs and runbooks, and provide higher-order production support during business hours.