Top Data Jobs in Singapore

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.

Build and maintain end-to-end data pipelines and medallion data lake architectures on Databricks and AWS. Implement data governance with Unity Catalog, ensure data quality, prepare analytics-ready datasets, support basic ML pipelines, and collaborate with stakeholders to meet reporting and BI needs.

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.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

Manage client relationships as a subject matter expert, collaborating with Account Executives to drive revenue, engage clients, and provide product insights for innovative solutions.

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.

Lead the development and deployment of Generative AI applications, collaborate with teams to deliver business use cases, and enhance data science skills.

The Data Scientist will identify new data sets, build processes for data collection, analyze data for potential applications, and research alpha signals for portfolio managers.

The Data Analyst will analyze financial datasets, create data pipelines, engage with vendors, automate data checks, and support investment teams.

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

Abstract and enter clinical data from healthcare records, apply clinical operations policies, troubleshoot VPN/MFA access, maintain confidentiality, and provide guidance to less-experienced team members while ensuring data quality and workflow adherence.

Senior Application Solutions Sales Specialist responsible for driving enterprise application sales, building client relationships, coordinating with technical and delivery teams, and meeting revenue targets. Represents NTT DATA's application and digital services in a hybrid working model.

Lead and deliver multiple concurrent projects or programs from concept to implementation across geographies and technologies. Manage stakeholders, budgets, scope, change control, risks, issues and escalations. Act as primary client contact, ensure quality and satisfaction, coordinate teams, and support pre-sales and proposals when required.

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.

Embed with strategic customers to design, deploy, and operate large-scale distributed storage and AI infrastructure. Debug performance and networking issues, write code and automation, collaborate with customer engineers, and translate operational requirements into product improvements to ensure successful production deployments.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

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.

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.

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.

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.

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.

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.