Top Data Jobs in Singapore

As Product Manager, you will own the vision and roadmap for Mastercard's Responsible AI and Privacy Enhancing Technologies Toolkit, ensuring product features align with governance, privacy, and regulatory expectations, while driving adoption and product outcomes.

The Enterprise Account Executive, Acquisition role focuses on developing a sales strategy within a territory for new customer acquisition, meeting sales targets, and collaborating with Solutions Architects and Professional Services teams.

Develop and maintain data pipelines and solutions, optimize data structures, build software components, and integrate AI applications. Requires experience in data engineering and strong technical skills.

This role involves building and maintaining data pipelines, developing ETL processes, optimizing data structures, and utilizing AI for enhanced data analytics.

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.

As a Principal Data Scientist at Micron, lead the development of smart manufacturing AI solutions, overseeing factory scheduling, optimization, and simulation to enhance operational performance.

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.

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.

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.

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.

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.

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, 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 FP&A data engineering: build automated pipelines from payment systems/ERP to cloud warehouses, ensure data integrity, design live dashboards and automated forecasting using SQL, Python, and AI/LLMs, and partner with engineering to embed finance logic across reporting and models.

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 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.

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 analytics and data design for regulatory and financial crime reporting. Build data foundations, validation frameworks, automated test suites, and snapshot/versioning for reproducible reports. Perform deep-dive analyses for anomalies and audits, shape a scalable reporting and risk analytics platform, and partner with cross-functional teams while mentoring adjacent analysts and data scientists.

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 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.