Top Data Jobs in Singapore

Design, build, test, deploy, and maintain scalable, resilient cloud-based data pipelines and microservices (primarily on AWS). Implement ETL/ELT, data lake/warehouse solutions, support analytics integration, enforce data quality, and follow Agile DevOps practices with CI/CD and IaC.

Act as primary contact for exchanges and market-data vendors, support licensing, ensure compliant data usage, coordinate audits, translate contract terms into operational requirements, and collaborate with technology, legal, and sourcing teams to maintain licensing coverage.

Designs and delivers data architecture solutions, creates secure production code, evaluates technologies, guides architecture governance, and applies AI-assisted practices to improve data frameworks, resiliency, and security.

Work with platform users, analysts and data engineers to design, test and document data models, pipelines and BI solutions. Implement data validation, reconciliations and controls, support ad-hoc analysis and external financial reporting to maintain a scalable, reliable data platform.

Design and deploy real-time ML models and credit risk frameworks to detect fraud and assess merchant lending risk. Translate business needs into scalable analytics, monitoring, and decision-support tools. Partner with product, engineering, and operations to productionize models and improve risk visibility and decision quality.

Manage privacy operations including data subject rights (DSR) intake and responses, PIAs/DPIAs, RoPA/data inventories, vendor privacy reviews, privacy tooling, metrics, and incident support to maintain global privacy program compliance.

Serve as ASOs single front door for Operations demands across Asia, translating business needs into prioritized initiatives, managing demand pipeline, shaping improvement using AI/data/APIs, and coordinating stakeholders to deliver operational efficiency, compliance, and value realization.

Lead the development of AI/ML solutions for production planning and agentic systems, mentor junior data scientists, and optimize performance and efficiency of systems.

As an intern, apply data analytics and machine learning to analyze semiconductor data, build models, and communicate insights to teams.

Lead technical strategy for payments optimization to balance conversion, fraud risk, and cost. Design and implement advanced optimization algorithms, guide experimentation and causal inference, collaborate with product and engineering to deploy ML systems at scale, influence product strategy, and mentor junior data scientists.

Lead architecture of a governed, reusable data, knowledge, and skills platform on Databricks to power analytics, AI agents, and real-time decisioning. Design data, semantic, and skills layers, enforce Governance-as-Code, enable regional data residency, and build agent interfaces and APIs while partnering with Data Science, Product, and Risk teams.

Lead architecture, development, and operation of Airwallex's data and AI platforms. Drive company-wide data platform solutions, build scalable multi-region pipelines, enforce governance and security, mentor the team, advocate best practices, and influence technical roadmaps to enable AI/ML-driven business impact.

Lead the Realtime Data Platform team to define a 1–3 year technical roadmap, modernize the core platform for petabyte-scale real-time analytics, partner with product teams to enable data-driven features, scale and structure engineering teams, and serve as a trusted technical advisor across Data and AI initiatives.

Design and build scalable batch and streaming ETL pipelines and data models, collaborate with stakeholders to translate data needs, ensure data quality and governance, and own end-to-end delivery for Knowledge Platform initiatives in Singapore.

Lead architecture, development, and operation of Airwallex's data and AI platforms. Drive company-wide data platform strategy, build scalable multi-region data pipelines, promote best practices, mentor engineers, and enable data-driven decision making and AI readiness across the organization.

Design and build scalable batch and streaming ETL pipelines and data models. Partner with engineers and business stakeholders to deliver reliable SSOT data, ensure data quality, governance, and support ML/AI use cases. Own end-to-end pipeline design, monitoring, and ongoing improvements.

Build and deploy end-to-end machine learning solutions for payment and fraud risk: translate business needs into ML problems, perform data and feature engineering, train and deploy models, analyze issues, develop ML platforms/tools, and collaborate cross-functionally to deliver business impact.

Partner with Product and Engineering to analyze large datasets, run experiments, and apply statistical methods to measure product performance, identify growth opportunities, set goals and forecasts, and drive product strategy through data-driven recommendations.

As a Senior Data Scientist, you'll analyze large datasets using advanced mathematical and statistical methodologies to derive actionable insights and optimize semiconductor operations.

Lead the data-quality stream to deliver CDE metadata, governance and audit‑ready artefacts for BCBS239 compliance. Manage a multidisciplinary team, engage senior stakeholders, run governance and change initiatives, and build Power BI monitoring dashboards. Translate data governance and lineage concepts into implementable controls and ensure global adoption across business and functional areas.

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.

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.

The Control and Metrics External Data Analyst will manage external data usage, oversee external data initiatives, and support the Chief Data Officer in implementing the Bank's data strategy.

As a Data Scientist, you'll develop predictive models, analyze large datasets, and collaborate with stakeholders to drive data-informed business decisions.