Top Data Jobs in Singapore

Lead transformation of actuarial processes through automation, analytics, and AI. Identify use cases, define requirements, support solutioning, testing and UAT. Manage actuarial data and build reusable analytics pipelines for persistency and claims, improving data quality, lineage and reporting. Support AI pilot delivery and scaling for actuarial reporting and MI.

Lead modernization of actuarial reporting through automation, process redesign, enhanced analytics and AI. Manage PACS/FFP+ projects, define actuarial AI roadmap, deliver pilots and scaled solutions, and coordinate cross-functional stakeholders to improve reporting efficiency, controls, and actionable insights.

Design, build and test prototypes using emerging technologies (AI/GenAI, autonomous agents, multimodal AI, quantum). Collaborate with product, design, and engineering teams to iterate, showcase proofs-of-concept, and drive adoption across the bank while researching frontier tech and enabling rapid experimentation.

Lead strategic foresight and innovation intelligence: research emerging trends, generate actionable insights, build and run sensing communities, engage external ecosystem, and present recommendations to senior leadership to inform DBS's innovation strategy.

The International Sector Analyst will conduct deep research to provide insights on industries, support investment decisions, and collaborate with data scientists and investment professionals.

The Network Technology Sales Specialist engages with clients, identifies opportunities, presents solutions, manages sales processes, and fosters relationships with senior executives to drive growth for NTT DATA.

The role involves analyzing datasets, developing dashboards, building data pipelines, and collaborating with teams to translate findings into business strategies.

Conduct data analysis and machine learning to improve account safety on WeChat, track fraudulent accounts, and detect anomalies.

Lead commercial technology and data initiatives for EMEA commercial teams: manage cross-functional projects, drive adoption of SFA/TPM/CRM tools, ensure compliance (SOX, GDPR), perform business analysis, change management, stakeholder engagement, and SLA/vendor management.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Lead complex analytics for global complaint vigilance: perform trend and risk analyses, build dashboards, support data ingestion and data-lake strategy, present findings to QA and cross-functional partners, and enable corrective action and regulatory responses.

Lead data science workstreams to build production-ready deep learning and probabilistic models integrated with multi-physics simulations. Own data preprocessing, scalable data pipelines, model architecture, deployment, cross-functional collaboration, customer-facing co-development, internal R&D, and mentoring of junior team members.

Lead development and deployment of deep learning and probabilistic models for multi-physics engineering problems. Architect scalable data pipelines, collaborate with simulation engineers, drive R&D, mentor junior team members, and work directly with customers to integrate models into production, including onsite customer collaboration and presentations.

Design, develop, and deploy data science and AI solutions for HDB; lead model selection and implementation, collaborate with stakeholders and engineers, improve team workflows, and maintain high technical standards across projects.

Lead technical delivery of electrical systems for newbuild and infrastructure fit-out projects (preferably data centers) across APAC. Review and QA design documents in BIM360/3Dx, coordinate with clients/contractors/vendors, perform electrical/plumbing/fire protection analysis, support design-for-manufacture, run thermal/hydraulic/CFD studies, maintain deliverables and revision control, and ensure compliance with standards and owner requirements.

The role involves managing data ingestion pipelines, collaborating with scientists for data optimization, and ensuring efficient data collection to support AI model training.

Lead rollout of APAC data culture and literacy strategies, design and deliver engagement and training initiatives, produce executive communications and presentations, coordinate cross-functional multi-country deliverables, and support stakeholder management to drive data-driven decision-making.

Design and deliver end-to-end data architectures and platforms (data lakes, warehouses, lakehouses) for asset management and predictive maintenance. Build ETL/ELT, streaming and API integrations, ensure data governance, security, quality, lineage, and observability, and provide technical leadership to enable analytics and data-driven decision-making.

Maintain and update security instruments, counterparty and general static data; execute control and client delivery frameworks; handle exceptions/escalations; report team statistics; perform ad-hoc tasks and projects. Ensure SOP compliance and support data management initiatives.

Conduct research on ML, deep learning, recommendation algorithms and AI agents for game data; perform large-scale statistical analysis, user behavior mining, sentiment analysis, topic modeling and summarization; identify retention pain points; improve data pipelines and develop distributed, efficient data-mining solutions.

Lead operational execution of data quality and governance for risk data. Manage data issue lifecycle, perform profiling and root-cause analysis, implement rules and monitoring, support data stewardship, drive BCBS239 attestation, collaborate with tech and risk units, and optimize tools and processes to ensure data fitness and regulatory compliance.

Design, build, deploy and monitor statistical and ML models across the full lifecycle. Partner with business, engineering, and risk to translate problems into analytics, ensure production-grade pipelines, mentor junior staff, and uphold data quality and responsible AI 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.

Design, build, and maintain scalable data lakes, databases, and ingestion pipelines for credit and lending data. Ingest and map external financial datasets, implement monitoring and alerting, translate stakeholder needs into data flows, and deliver analytical insights that drive product quality and business value.

Support EDB Finance by improving and automating incentive administration workflows. Co-design systems and dashboards, review company claims for compliance, perform on-site assessments, prepare reports to senior management, identify policy gaps, and promote incentive governance and risk management.