Top Data Jobs in Singapore

Lead design and delivery of scalable batch and streaming data pipelines for Growth use cases. Improve ingestion, scheduling, and pipeline efficiency; integrate third-party sources; ensure data quality; collaborate with product, engineering, and BI to translate business needs into platform solutions.

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.

Intern will perform data analysis and develop predictive models using machine learning for semiconductor manufacturing datasets, contributing to insights and decision-making.

Manage, maintain, and optimize critical database systems (SQL Server, Oracle). Perform installs, patches, backups, access control, monitoring, performance tuning, incident/change/problem management, on-call support, capacity planning, automation, reporting, and collaborate with global teams and site stakeholders.

Lead design and implementation of process-mining and labor data engineering for Front End operations. Build digital footprint capabilities, dashboards, AI-driven optimizations, and standardized processes to drive labor productivity, savings, and scalable operational improvements across global sites.

Develop machine learning, simulation, and optimization models to analyze manufacturing, equipment, and process data. Build scalable analytics products, dashboards, and automated workflows. Partner with cross-functional engineering teams to improve equipment efficiency, factory productivity, and drive operational excellence through data-driven insights and recommendations.

As a Data Science Engineer, you will analyze large datasets, develop predictive models, and work collaboratively to enhance data tools and processes.

Analyze semiconductor manufacturing data to identify yield detractors, build data pipelines, apply statistical and machine learning models for yield improvement, support DOE experiments, and create automated dashboards and reports for engineering stakeholders.

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

Develop end-to-end data science and ML solutions for semiconductor manufacturing to improve yield, quality, cycle time, and reduce cost. Work across the full pipeline from data acquisition and cleansing through model building, deployment, visualization, and collaboration with international engineering teams. Leverage statistical modeling, deep learning, generative AI techniques, and manufacturing domain knowledge to drive high-impact projects.

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 design and delivery of enterprise-grade factory scheduling, optimization, and simulation solutions. Architect global scheduling systems integrating optimization, discrete-event simulation, and reinforcement learning. Provide data analytics, drive cross-site alignment, benchmark solutions, influence senior leaders, and deploy production systems that improve manufacturing metrics.

Drive labor productivity through program management, data analysis, automation, and AI methodologies to enhance operational efficiency and reduce labor hours.

Lead design and development of scalable data infrastructure and self-service tooling for data engineering teams. Provide technical leadership, implement robust systems (Kubernetes/Terraform/GitOps), ensure quality through testing and maintenance, troubleshoot production issues, and collaborate cross-functionally to deliver reliable data platforms.

Perform data exploration, statistical analysis, and visualization on FOUP (wafer carrier) transportation datasets to identify factors affecting transport time. Engage stakeholders, develop methodology and optimization recommendations, and present findings.

Join Micron as a Data Scientist to apply data analysis and machine learning expertise toward innovations in memory, storage, AI, and related products. The posting emphasizes company mission, inclusion, and application process; specific role responsibilities and qualifications are not listed.

As a Computer Vision Engineer, you will develop image processing solutions, apply machine learning techniques, and collaborate on engineering projects to enhance manufacturing innovation.

Partner with Product and Engineering to analyze large datasets, run experiments, build statistical models, define product metrics, forecast outcomes, and deliver insights that drive product strategy and roadmap decisions.

Lead design and build of high-performance distributed data infrastructure and AI enablement platforms. Optimize systems internals and JVM performance, implement lakehouse and real-time streaming, develop scalable vector indexing and AI knowledge platform, own SDLC for petabyte-scale systems across global regions, drive engineering best practices, and mentor mid-level engineers.

Lead analytics for regulatory and financial crime reporting: design data logic, validation and testing, enable reproducible historical reports, investigate anomalies and audits, and build scalable reporting and risk analytics with cross-functional partners.

Lead design, build, and operate distributed, large-scale (batch/streaming) data platforms and pipelines. Drive technical decisions, performance optimization, data architecture (lakehouse), tooling standards, third-party integration, and mentor junior engineers to enable company-wide data-driven capabilities.

Lead a Singapore-based team to design, build, and maintain scalable data infrastructure and self-service developer tooling. Implement robust, maintainable systems, ensure quality through testing and troubleshooting, collaborate cross-functionally, and mentor engineers while staying current with emerging technologies.

The Managing Principal will lead data projects, define client data strategies, conduct capability assessments, and influence data-driven culture in financial services.

As a Data Scientist at Micron, you'll develop AI-driven solutions in semiconductor manufacturing, build predictive models, and communicate analytical insights to stakeholders.

The Senior Data Scientist will develop predictive models, implement machine learning solutions, optimize production processes, and mentor junior staff to enhance data-driven decision-making in semiconductor manufacturing.