Top Data Jobs in Singapore

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.

Support market intelligence by collating, cleaning, and automating competitor and market datasets. Build Python data pipelines, maintain dashboards (Power BI/Excel), assist competitive analysis, explore AI-assisted workflows, and coordinate cross-functionally to ensure data quality and reproducibility.

Lead Group Market Data category and IT software strategic sourcing: establish governance, optimise spend and licensing, drive sourcing strategies, negotiate complex vendor contracts, manage vendor relationships, and partner with Technology, Risk, Finance and business stakeholders to deliver compliant, cost-effective outcomes.

Prepare month-end closes, forecasts, variance analysis, account reconciliations and profitability reviews. Provide insights and recommendations, support budgeting, analyze project and departmental costs, and identify cost-management opportunities for international operations.

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.

Design and develop cloud-native, reusable AI and data products for Singapore government projects. Prototype, implement, and validate ML algorithms (CV, NLP, recommender, synthetic AI), build microservices, deploy to cloud and edge (mobile/IoT), assess AI maturity, collaborate with research and industry partners, document and transfer technology, and support product lifecycle and operationalisation.

Senior individual contributor leading global commercial risk and insurance programs. Performs risk identification, advanced analysis, mitigation strategy design, insurance placements and claims oversight. Partners with Legal, Finance, Operations and external brokers, mentors junior staff, delivers training, and supports crisis response and enterprise risk decision-making.

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.

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.

This role focuses on driving enterprise data governance, including policies, training, AI governance, and collaboration with technology teams to implement data management practices.

As a Senior Associate Client Manager, you will manage client relationships, drive expansion and renewals, and ensure satisfaction through effective communication and sales strategies using Salesforce.com and other tools.

The intern will support APAC growth initiatives, analyze data with Python/R and SQL, and design BI dashboards using Power BI, while assisting in program management tasks.

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

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.

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.

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 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.