Top Data Jobs in Singapore

Facilitate online undergraduate learning in statistical data analysis for business. Guide students in data collection, descriptive and inferential statistics, visualization, probability, hypothesis testing, correlation, regression, and evidence-based decision-making. Responsibilities include conducting online sessions, providing academic and subject guidance, marking assessments, managing discussion forums, supporting academic writing and research skills, and responding promptly to student queries.

Leads the enterprise strategy, roadmap, operating model, and delivery of data products and Data-as-a-Service capabilities. Oversees data product engineering, governance, security, adoption, monetisation, and value measurement across the bank. Establishes a Data Products Centre of Excellence, builds cross-functional teams, enables self-service data consumption, and partners with senior stakeholders, technology, risk, compliance, and governance teams to deliver scalable, controlled, and commercially valuable data capabilities.

Supports electrical engineering design delivery for data center and mission-critical projects across APAC. Responsibilities include defining project objectives, schedules, resources, and deliverables; applying engineering judgment; managing technical risks and quality standards; mentoring team members; supporting client relationships; and contributing to bids, proposals, thought leadership, and regional service delivery.

Leads data-driven industrial optimization projects from requirements gathering through deployment and monitoring. Responsibilities include building scalable data pipelines, integrating industrial data from IoT devices, sensors, test benches, and SCADA systems, performing data quality checks and exploratory analysis, developing machine learning models, creating Power BI and Flask dashboards, supporting digital twin simulations, and developing RAG-based chatbot solutions.

Early-career data scientist role to analyze user and content data, build metrics, design recommendation strategies (recall, ranking, cold-start, diversity), run A/B tests, evaluate experiments, explore LLM/multimodal applications, and improve data pipelines and feature logging.

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.

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.

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, 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.

Manage employment screening, reference checks, screening-vendor governance, work pass administration, RNF licensing, employee declarations, regulatory reporting, and HR compliance processes. Maintain records, procedures, dashboards, and metrics while ensuring data privacy and regulatory compliance. Partner with Compliance, Talent Resourcing, vendors, and other stakeholders to resolve issues, support audits, monitor service levels, and improve HR processes and employee experience.

Collects, validates, analyzes, and visualizes APAC digital and e-commerce data to produce dashboards, reports, and actionable business insights. Partners with marketing, product, e-commerce, distribution, and agency teams to measure KPIs, support digital growth strategies, manage brand health reporting, and improve reporting processes. Presents findings to stakeholders and senior management while managing agency deliverables.

Design and maintain data pipelines, build data warehouse models, optimize dbt Cloud workflows, improve CI/CD and DevOps practices, and support AI initiatives involving Data Genie. Collaborate with business stakeholders to resolve data issues, deliver actionable insights, and support operational needs across business units.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Leads VAST Data’s APJ pre-sales function, personally supporting complex AI infrastructure opportunities and executive customer engagements. Builds, coaches, and retains a distributed regional solutions engineering team; sets technical strategy; partners with sales, channels, alliances, product, and engineering; influences roadmap through customer and competitive insights; and represents VAST with partners, analysts, press, and the NVIDIA ecosystem. Requires extensive APAC travel and a Singapore base.

Analyzes sales channels, business performance, revenue, and acquisition trends; develops dashboards and reports; designs and calculates sales incentive programs; monitors targets; and presents actionable insights to stakeholders. The role collaborates with Sales, HR, and other business teams, supports strategic decision-making, and applies banking and wealth management industry knowledge to identify optimization and innovation opportunities.

Own data and AI product initiatives end to end, from defining problems and data requirements through coding, evaluation, launch, monitoring, improvement, and adoption. Build production systems with AI coding agents, create release evaluation suites, track product and operational metrics, measure business impact, collaborate with technical and business teams, and document products through runbooks, design notes, evaluation reports, and training materials.

Support data transformation, structure, metadata, and workflow processes. Extract and analyze transaction, marketing, app usage, and financial data. Build interactive visualizations and reports by integrating KPIs from multiple sources, enabling business teams to self-serve insights and helping stakeholders answer questions about business performance.

Lead cost management for complex construction projects from initiation through completion. Responsibilities include cost planning, estimating, reporting, forecasting, value engineering, lifecycle costing, budget and risk management, contract administration, invoice coordination, stakeholder engagement, team leadership, client management, and business development. The role oversees multidisciplinary teams, ensures financial and delivery controls, presents cost plans and reports, and develops cost managers while supporting client objectives and business growth.

Design and build scalable cloud-native data pipelines and lakehouse solutions using Spark, PySpark, Apache Iceberg, streaming technologies, Python, shell scripting, and SQL. Modernize legacy workloads, migrate systems to cloud architectures, implement data quality and monitoring automation, and support metadata, lineage, and governance through open catalogue frameworks. Collaborate with analysts, data scientists, and stakeholders to deliver reliable, high-performance data solutions.

Design and build cloud-native data pipelines, lakehouse solutions, and real-time streaming systems using Spark, PySpark, Iceberg, Python, and SQL. Modernize legacy workloads, migrate processing systems to cloud architectures, automate ETL/ELT workflows, and implement data quality, monitoring, governance, metadata, and lineage practices. Collaborate with analysts, data scientists, and stakeholders to deliver reliable, scalable data solutions and troubleshoot pipeline performance and operational issues.

The role involves leading BIO initiatives, collaborating with sales teams, enabling digital capabilities, and engaging stakeholders to enhance agent productivity and business outcomes.

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.

Design and deploy computer vision and deep learning solutions for manufacturing inspection and monitoring. Extract and clean large datasets, build multimodal AI models, apply MLOps for production deployment, and collaborate with cross-functional teams to translate research into operational systems and documentation.

Design, build, and maintain scalable data pipelines, data models, feature stores, and data catalogues to support AI model training and inference. Ensure data quality, lineage, governance, and secure integration of diverse real-time and batch transport data sources. Collaborate with AI architects, infrastructure engineers, and stakeholders to deliver production-grade data products and maintain pipeline reliability.