Top Data Jobs in Singapore

Summer internship applying data science, AI, software engineering, analytics, and automation to manufacturing and business problems. Interns analyze datasets, build dashboards/reports, develop automation or software solutions, and present findings to improve operational efficiency and support digital transformation.

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.

Work at the intersection of data, operations, and business to identify, prioritise, and resolve data quality and operational issues. Build SQL/Python-based analytics, dashboards, and AI-enabled solutions; perform root-cause analysis; partner with stakeholders to deliver scalable fixes and maintain data governance and controls.

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.

Lead large-scale payment data analyses to identify optimization opportunities and support A/B testing. Build scalable ETL pipelines, automation, and self-service analytics tools. Partner with product, data, and commercial teams to deliver actionable insights, mentor peers, and communicate results to technical and non-technical stakeholders.

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.

Design and implement advanced smart manufacturing solutions in scheduling, mathematical optimization, and discrete event simulation. Build data analytics and applications to provide actionable insights, collaborate globally to deploy solutions across manufacturing sites, and integrate AI/OR hybrid methods to improve production performance and benchmarking.

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

Develop and deploy product-disposition workflows and deviation alert systems using statistical tools and ML/AI to improve yield, reliability, and quality. Build algorithms for data mining, pattern recognition, and wafer/die screening. Collaborate with Fab, design, and quality teams, mentor team members, and drive technical innovation to meet KPIs like quality, cost, cycle time, and scale.

Design and deploy computer vision and deep learning models (CNN, LSTM, transformers) for industrial inspection and anomaly detection; extract, clean, and analyze large multimodal datasets; implement MLOps (MLflow, Airflow, Docker) for production deployments; collaborate across engineering, operations, and quality teams; mentor engineers and contribute research outputs and technical documentation.

Support investment teams by acquiring, cleaning, and analyzing diverse datasets to test investment theses. Learn fundamental investor approaches, identify key data drivers and inflection points, and present research findings. Work with existing and new data to generate insights and decision-support tools for sector-focused investment research.

Design, implement, and maintain data-driven processes and analytics solutions. Collect, cleanse, automate, and prepare data from disparate sources. Build KPIs and dashboards, apply statistical and machine learning methods, collaborate with stakeholders, perform testing and deployment, and train users to enable data-driven decision making and process improvements.

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

Lead analytics and experimentation for payments: design and run frontend experiments, quantify growth opportunities, build measurement frameworks and north-star metrics, translate business problems into data science projects, communicate insights to stakeholders, and mentor junior data scientists while owning cross-functional initiatives.

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.