Top Data Jobs in Singapore

Lead credit risk analytics for business lending: monitor portfolio performance, identify emerging risks, support portfolio-level credit strategies, prepare reports and dashboards, collaborate with operations and product, contribute to stress testing, regulatory reporting, and governance.

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.

Lead design and implementation of cloud DevOps strategy for global Data and AI infrastructure. Build observability and detection capabilities, enable self-service tooling for data teams, manage scalable, secure infrastructure, and align DevOps practices and standards across geographies.

Design and implement smart manufacturing AI solutions for advanced factory scheduling, optimization, and simulation. Build analytics and applications, apply new algorithms, collaborate across global sites, drive benchmarking, and support continuous improvement of production metrics.

The Data Scientist will optimize semiconductor processes, analyze data, develop visualization tools, and support production through advanced analytics and modeling.

Processes and manages customer records and information as part of Iron Mountain’s operations services. The role supports data handling, digital transformation, records management, data privacy, and related operational workflows. The posting emphasizes opportunities for career development and contributing to sustainable solutions, but provides no specific duties, qualifications, technologies, salary, travel, or clearance requirements.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Designs and maintains conceptual, logical, physical, analytical, and dimensional data models supporting reporting, analytics, AI, and business decisions. Develops source-to-target mappings, transformation logic, data dictionaries, and integrated data assets. Profiles data sources, creates analytics tables, supports ingestion and transformation processes, and contributes to data quality, metadata, lineage, and governance. Collaborates with analysts, technology teams, and data platform teams to deliver scalable, reusable enterprise data solutions.

Own NVIDIA’s strategic alliance across APJ, serving as the primary relationship leader and defining regional engagement strategy. Execute co-selling, campaigns, executive briefings, customer programs, and events to generate qualified pipeline, influence deals, and grow partner-sourced revenue. Adapt engagement models across Japan, Korea, India, Southeast Asia, and ANZ while collaborating with sales, marketing, solutions architecture, product, and channel teams. The role requires strong AI infrastructure expertise, independent execution, and frequent APJ travel.

Support autonomous-vehicle data analysis by mining vehicle logs for scenarios and edge cases, building ETL pipelines, developing internal dashboards, and exploring AI agents for automated analysis and scenario generalization. The internship requires Python, Linux, SQL, and database knowledge, with bonus experience in web development, frontend tools, visualization, LLMs, Git, or Docker. Students must commit to a four- to six-month internship.

Design, validate, and deploy AI algorithms for digital health projects. Lead technical innovation, support data platform development and retrospective analysis, collaborate with clinicians and biostatisticians, publish findings, prepare technical reports, and mentor junior AI researchers.

Lead company-wide performance intelligence: build central dashboards and KPI frameworks, produce executive reports, run deep metric analyses (P&L, funnels, retention), create forecasts and ROI models, and design self-serve data infrastructure and automation to guide strategic decisions and resource allocation.

Design, build, and optimize offline and real-time data pipelines and warehouses for product data. Lead end-to-end R&D for online product data pipelines, ensure timeliness and accuracy, perform Flink-based real-time processing and performance tuning, and enable business growth through data products and services.

Design, build, and maintain analytics-ready data marts using dimensional modeling; partner with analytics and business teams to deliver documented datasets; implement resilient batch and real-time data pipelines; architect cloud data infrastructure; enforce data standards, validation, and monitoring to ensure data integrity and scalability.

Build and maintain the risk-control data warehouse, develop thematic metrics and indicators, design offline and real-time data architectures, optimize data pipelines, and deliver reporting and API interfaces for the data mart to support risk control business lines.

Lead development and deployment of GenAI, RAG, ML and Agentic AI solutions for continuous audit, risk assessment, testing and reporting. Collaborate with auditors, data engineers and cross-functional teams to design, evaluate, and scale production-grade models and MLOps on cloud infrastructure. Introduce innovative analytics to improve audit effectiveness and coach stakeholders.

Design, develop, and maintain data infrastructure microservices using C++, optimize for performance, debug issues, and collaborate with teams.

Take end-to-end ownership of backend features and SaaS services in a microservices architecture. Design, implement, deploy, and operate scalable, reliable Node.js services. Work with Redis Streams, MongoDB, Kubernetes, and ensure test coverage, performance tuning, and collaboration with cross-functional teams.

Lead end-to-end cost management for large-scale data centre and mission-critical projects. Define cost strategies, manage cost planning, estimating, forecasting, contract administration and commercial risk. Act as client lead, mentor cost teams, drive value engineering, controls and governance, and support business development in the data centre sector.

Evaluate data centre investment opportunities, build and maintain financial models, prepare investment memos and presentations, perform market research and due diligence, coordinate external advisors, and provide ad-hoc portfolio and performance analysis to support senior management.

Design, build, and operate backend services and data pipelines to ingest, process, enrich, and deliver large scientific, media, and geospatial datasets. Implement REST APIs, event-driven and streaming systems, and Kubernetes-based production infrastructure to support machine learning and agentic AI applications. Collaborate with scientists and ML engineers to translate requirements into scalable, reliable solutions.

Lead mechanical design and engineering for data centre projects, manage multidisciplinary teams and budgets, engage clients, mentor junior engineers, and integrate innovative, energy-efficient solutions.

Lead electrical design and engineering for data centre projects in Sydney. Oversee project delivery, manage budgets and clients, mentor junior engineers, and integrate industry innovations for energy-efficient, high-performance facilities. Support multidisciplinary teams and foster client relationships.

Provide L3 managed services for cross-technology client infrastructure: resolve complex incidents, ensure SLA compliance, mentor junior staff, create knowledge articles, collaborate with vendors, drive automation and operational improvements across cloud, security, networking and application domains.

Provide hands-on network implementation, configuration, installation and break/fix troubleshooting. Own portions of installations, escalate complex issues, document SOPs, maintain project administration, present to clients, and work toward professional networking certifications.