Top Data Jobs in Singapore

Develop and deploy predictive models and AI/agentic AI solutions using large-scale manufacturing data. Perform EDA, data extraction/cleansing, feature engineering, and statistical modeling. Collaborate with data engineers, manufacturing engineers, UX, and stakeholders to translate insights into operational improvements that boost yield, quality, efficiency, and business value.

Develop advanced analytics solutions for High Bandwidth Memory manufacturing. Analyze engineering datasets, build automated data pipelines and monitoring workflows, apply statistical and machine learning methods to detect deviations, investigate process-to-product relationships, and create dashboards that improve yield, quality, reliability, and performance insights. The intern will present findings to engineering stakeholders and gain experience in semiconductor product engineering, manufacturing analytics, and AI-enabled engineering solutions.

Serves as the technical specialist for EHSS data, designing data models, mappings, transformation logic, quality controls, metadata, and reusable datasets. Partners with subject matter experts, IT, and analytics teams to deliver trusted data products supporting reporting, analytics, automation, AI, and operational decisions. Responsibilities include validation, reconciliation, root-cause analysis, testing, deployment readiness, governance, documentation, and long-term sustainment of enterprise data assets.

Lead data engineering and process-mining initiatives to capture Digital Footprints, generate actionable visualizations and AI-driven optimizations, standardize scalable digital processes across Front-End sites, and track productivity and labor-hour savings via dashboards and cross-functional execution.

Partners with manufacturing, planning, and supply chain stakeholders to solve complex operational problems. Designs and deploys digital twins using operations research, mathematical optimization, and discrete event simulation. Develops production-grade applications, data pipelines, models, APIs, and user interfaces. Converts large datasets into decision-support tools, drives solution deployment across global manufacturing sites, and collaborates with data scientists, AI engineers, product owners, and domain experts.

Operate and maintain critical database systems supporting manufacturing and engineering. Responsibilities include database installation, upgrades, patching, access management, backups, monitoring, performance tuning, incident resolution, disaster recovery, capacity planning, reporting, automation, and business continuity. The role provides on-call support, collaborates with customers on database requirements, improves operational reliability, and evaluates emerging database technologies and AI-assisted tools.

Build scalable batch and real-time ETL pipelines, data models, and data products for Airwallex’s Customer Data Platform. Develop trusted data foundations across warehouses and cloud infrastructure to support analytics, machine learning, operational decision-making, business intelligence, and AI applications. Partner with globally distributed teams on complex technical work and apply data engineering best practices.

Build scalable batch and streaming ETL pipelines for Airwallex’s Customer Data Platform. Design data foundations, schemas, and models across databases and warehouses to support business intelligence, machine learning, operational decisions, and AI applications. Partner with globally distributed teams on complex technical projects while applying strong problem-solving and collaboration skills.

Lead quantitative analysis, experimentation, and statistical modeling to guide product and business decisions. Build scalable analytics systems and decision frameworks, partner with cross-functional teams, define success metrics, and measure initiative impact. Communicate insights to executives, influence product strategy and roadmaps, and solve ambiguous problems using large datasets. The role also contributes to machine learning, AI, experimentation, and production decision-support systems.

Designs and owns scalable batch and streaming data pipelines, data models, and infrastructure for business and AI use cases. Partners with engineering and cross-functional teams to deliver reliable solutions, monitoring, governance, and data quality improvements. The role involves distributed data systems, real-time analytics, knowledge retrieval, and AI-ready infrastructure, with work based five days per week in Singapore.

Own regional data center vendor strategy and end-to-end colocation deals, including planning, RFPs, commercial negotiations, execution, vendor relationship management, QBRs, budgeting, spend review, and invoice approval. The role coordinates with legal, operations, capacity planning, network strategy, and security teams across multiple geographies to expand and optimize Cloudflare’s data center footprint.

Lead modelling and analysis roadmap for FX products: forecast and monitor FX volatility, optimise trade execution with statistical/ML models, run customer and profitability analyses, and partner with product, trading, risk, and engineering to translate insights into trading and product decisions.

Leads engineering strategy, organization, performance, quality, and talent development for the CIS Domain in Singapore. Manages discipline heads across design, product ownership, software, cloud platforms, and innovation. Oversees engineering staffing, delivery, continuous improvement, Agile and Lean practices, digital development environments, and collaboration across multidisciplinary teams. Partners with domain leadership on business development and ensures engineering capabilities support cloud, software, AI, cybersecurity, and user-centric products and services.

Provides second-line oversight and credible challenge for AI, privacy, and data risks across APAC. Leads monitoring and testing reviews, control assessments, regulatory engagements, issue remediation, governance reviews, and executive reporting. Translates regulatory expectations into controls, testing methods, evidence requirements, and practical guidance while partnering with business, technology, legal, data, cybersecurity, and model risk stakeholders.

Leads technology and AI strategy for Microsoft education customers in Singapore. Advises senior executives, develops multi-year transformation roadmaps, orchestrates specialists and partners, and drives responsible AI, cloud, data, security, adoption, customer success, and business growth outcomes across education institutions.

Operate and engineer database systems supporting manufacturing and engineering. Responsibilities include installation, upgrades, patching, access management, backups, performance tuning, monitoring, incident resolution, disaster recovery, capacity planning, reporting, automation, and business continuity. The role provides on-call support, collaborates with customers on database requirements, improves operational reliability, and evaluates emerging database technologies and AI-assisted tools.

Lead analytics and data design for regulatory reporting and financial crime compliance. Build data models, validation frameworks, automated testing, QA playbooks, and self-service analytics in partnership with Compliance, Finance, DataOps, and Engineering. Investigate anomalies and audit findings, identify root causes, shape risk analytics platforms, and promote analytical rigor and documentation across global teams.

Lead analytical design for regulatory reporting and risk-compliance data infrastructure. Define data logic, models, validation frameworks, automated testing, and QA processes; investigate anomalies and audit findings; partner with compliance, finance, data, and engineering teams; shape scalable reporting platforms; and mentor analysts and data scientists.

Leads discovery and analysis for complex, cross-system technology initiatives. Translates business needs into requirements, process models, user stories, acceptance criteria, and solution designs. Coordinates stakeholders, backlog activities, testing, defect resolution, deployment readiness, transition, and post-production stabilization. Collaborates with product, architecture, engineering, business, and vendor teams while mentoring analysts and supporting knowledge transfer.

Analyze semiconductor manufacturing data to identify yield detractors, optimize processes, and reduce defects. Build data pipelines from SQL databases, sensor networks, and fabrication logs; apply statistical modeling, machine learning, SPC, DOE, and related analytics. Create automated dashboards and reports using Dash, Plotly, or Angular, and collaborate with manufacturing, equipment, process, and integration engineers to resolve production issues and drive continuous improvement.

Own an enterprise territory and manage full-cycle sales, from prospecting through negotiation and close. Build territory plans, navigate technical and executive stakeholders, quantify business value, and maintain accurate forecasts using Salesforce and MEDDPICC or Command of the Message. The role requires selling complex SaaS or PaaS solutions to enterprise customers, strong technical fluency, consistent quota overachievement, startup experience, and the ability to develop sales playbooks in a high-growth environment.

Leads the design and delivery of scalable, secure technology solutions across applications, integrations, and data platforms. Translates business requirements into technical designs, provides hands-on engineering guidance, conducts code and design reviews, and applies architectural and development standards. Partners with business, product, architecture, and infrastructure teams throughout Agile delivery. Oversees data modeling, pipelines, APIs, microservices, cloud and hybrid environments, security, performance, reliability, technical risk resolution, and mentoring of software and data engineers.

Analyze semiconductor manufacturing data to identify yield detractors, reduce process variation, and improve device yield. Build data pipelines and automated processes using data from SQL databases, sensors, and fabrication tools. Apply statistical modeling, machine learning, and DOE analysis to solve production issues and support root cause investigations. Create dashboards and reports with visualization tools, collaborate with process engineering teams, and responsibly use AI-enabled tools to improve manufacturing outcomes.

Summer analysts will build and deploy machine learning, generative AI, and agent-based solutions; integrate complex datasets; develop predictive models; run experiments; analyze trends; and deliver actionable insights. They will also support data governance, risk management, data quality, privacy, and regulatory controls while collaborating with agile, cross-functional teams. The program includes mentorship, training, and potential full-time opportunities after graduation.

Leads ticketing fees and data initiatives within a transit authority, including monitoring ticketing costs, managing provider contracts, analyzing transit data, supporting new payment modes, implementing service improvements, and preparing agreements and approval papers. The role also develops ticketing policies, monitors service levels and fees, and manages internal and external stakeholders while leading a team.