Top Data Jobs in Singapore

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.

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 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.

Architect and lead the Data, Knowledge, and Skills layers enabling analytics, AI agents, and real-time decision systems. Design governed Databricks-based data models, semantic layers/metric stores, agent interfaces, governance-as-code, and regional data localization to ensure compliance, quality, and consistent metrics across the business.

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.

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.

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

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.

The Principal Data Scientist will lead the development of digital twin technology integrating advanced simulation and predictive analytics, collaborating with engineers to optimize manufacturing processes.

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.

The Data Scientist will analyze big data, develop software solutions, identify insights, and enhance products/services through data-driven decisions.

The program develops skills in warehouse operations, focusing on GMP compliance, continuous improvement, SOP updates, and master data management for biopharmaceuticals.

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

Lead and deliver data engineering solutions: design and build data products, pipelines, warehouses and models; lead teams; implement cloud architectures; drive data mesh/fabric and DevSecOps practices; collaborate with business and data science; ensure reliability, monitoring, and documentation.

Lead commercial technology and data initiatives for EMEA commercial teams: manage cross-functional projects, drive adoption of SFA/TPM/CRM tools, ensure compliance (SOX, GDPR), perform business analysis, change management, stakeholder engagement, and SLA/vendor management.

Design, build, and maintain scalable data products, warehouses, and pipelines. Collaborate with data science, analytics and product teams to deliver ETL/ELT solutions, cloud-based architectures, and data models. Lead migrations, troubleshoot systems, implement data mesh concepts, apply AI/GenAI for automation, and participate in governance, documentation, and stakeholder communication to drive business value.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Lead complex analytics for global complaint vigilance: perform trend and risk analyses, build dashboards, support data ingestion and data-lake strategy, present findings to QA and cross-functional partners, and enable corrective action and regulatory responses.

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.

Design, develop, and deploy data science and AI solutions for HDB; lead model selection and implementation, collaborate with stakeholders and engineers, improve team workflows, and maintain high technical standards across projects.

Lead technical delivery of electrical systems for newbuild and infrastructure fit-out projects (preferably data centers) across APAC. Review and QA design documents in BIM360/3Dx, coordinate with clients/contractors/vendors, perform electrical/plumbing/fire protection analysis, support design-for-manufacture, run thermal/hydraulic/CFD studies, maintain deliverables and revision control, and ensure compliance with standards and owner requirements.

The role involves managing data ingestion pipelines, collaborating with scientists for data optimization, and ensuring efficient data collection to support AI model training.

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.