Top Data Jobs in Singapore

Ensure accuracy, consistency, and quality of master data across commercial systems. Manage master data lifecycle, enforce data governance and GDPR compliance, implement MDM systems, create Power BI/Excel reports, develop data quality controls, maintain business glossary and data lineage, and collaborate with Sales, IT, and compliance teams.

Develop and implement computer vision and machine learning models (object/change/anomaly detection, classification, behavior analysis, video stitching). Build POCs, run experiments in realistic environments, optimize model robustness, produce documentation and patentable ideas, stay current with AI advances, present findings, and (for senior profiles) provide technical mentorship.

Build and maintain logistics data pipelines, dashboards, and reports; validate and cleanse datasets; translate business requirements into scalable data models; perform analysis to identify trends and root causes; align metrics with global KPIs and governance; prioritize analytics demand and partner with cross-functional teams to improve visibility and logistics performance.

Design, build, and productionize ML models for credit scoring, fraud detection, and segmentation. Maintain model governance and documentation, develop scalable MLOps pipelines and monitoring, generate analytical insights and dashboards, and mentor junior data scientists while leading end-to-end data science initiatives.

Lead strategy and execution of data analytics and data science across the organisation: build and mentor teams, partner with cross-functional stakeholders, drive data-driven initiatives that improve risk management and business metrics, uplift tooling and capabilities, and ensure data governance and regulatory compliance across markets.

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.

Partner with product, UA, and engineering to design and evaluate A/B tests, build predictive models (LTV, churn, retention, segmentation), analyze player behavior, and deliver data-driven recommendations to improve engagement, retention, and monetisation. Build scalable data-science solutions and apply new AI techniques to drive product decisions.

Provide L2 cross-technology managed services support: monitor, investigate, and resolve incidents within SLAs; update tickets; execute changes and audits; work with vendors and automation teams; assist in disaster recovery and handle client escalations.

The Senior/Lead Data Engineer designs and optimizes data solutions on Alibaba Cloud, develops data pipelines, manages data warehouses, and ensures data quality and compliance.

Provide hands-on post-sales technical support for enterprise storage customers: troubleshoot, resolve, escalate issues, perform field services (installs/upgrades), manage feature requests/bugs, and collaborate with sales, professional services, and engineering.

The Associate Data Engineer will contribute to Machine Learning and NLP projects, collaborate with cross-functional teams, and enhance threat detection through data-driven intel.

Manage the design and lifecycle of Web3 infrastructure products focusing on data services, market data systems, and algorithm platforms. Collaborate with teams to meet performance and security needs, leveraging advanced AI technologies and on-chain data analytics.

The Infra Product Manager will develop algorithm platforms and Web3 search systems, integrate AI capabilities, analyze on-chain data, and ensure product delivery quality.

Lead architecture and delivery of post-trade data systems, designing near-real-time and historical data pipelines. Drive technical roadmap, mentor engineers, implement robust testing and monitoring, resolve incidents, and integrate analytics technologies to support trading product features and operational stability.

Design, build, and operationalise large-scale cloud data pipelines (batch and streaming) using Databricks/Snowflake and cloud platforms to support reporting, automated systems and AI/ML teams. Administer cloud data platforms, optimise SQL/storage, implement CI/CD, IaC, containerisation and serverless solutions, and collaborate with clients, partners and internal teams to scale data engineering deployments.

The Platforms and Data Engineer will develop and manage high-performance analytics solutions, design data transformation processes, maintain data systems, and support AI projects.

Sell security technology solutions by generating pipeline, engaging clients and stakeholders, leading workshops, supporting pre-sales, designing tailored security solutions, maintaining subject-matter expertise, managing account plans, and collaborating with sales and vendor partners to close deals and meet revenue targets.

Design, build, and maintain a unified data framework, scalable data pipelines, and data models. Improve data ingestion, quality, monitoring, and governance; troubleshoot pipeline issues; optimize performance; integrate third-party tools; and apply AI techniques to enhance data quality and engineering workflows.

The intern will solve deep learning and computer vision tasks, design and deploy models, develop tests, and communicate with the team.

Lead the development of AI and ML solutions for underwriting, manage a team of data scientists, and ensure compliance and governance in initiatives.

Seeking a Data Analyst to analyze data sets, generate reports, and support data-driven decision-making within the company.

Lead mechanical design and delivery for data center and infrastructure fit-out projects across APAC. Review and QA mechanical, plumbing and fire protection designs in BIM platforms, coordinate vendors and contractors, perform thermal/hydraulic/CFD analyses, manage scope changes, ensure compliance with standards, and support constructability and off-site manufacture activities while reporting to technical program leadership.

Develop, train, fine-tune, evaluate, and deploy AI/ML models and LLM-powered data products. Build end-to-end model pipelines, feature engineering, monitoring, and production deployment. Apply generative AI for summarization, classification, knowledge extraction and semantic search. Collaborate with product, engineering, and business teams and integrate third-party tools and open-source models.

The Staff Software Engineer will design high-performance backend services, manage distributed state, ensure system resilience, and implement cloud-native architectures with advanced engineering principles.

Design, develop, and deploy production-ready AI applications and scalable DataOps/MLOps pipelines for avionics manufacturing. Build LLM/RAG/agent-based solutions, integrate enterprise and manufacturing systems, implement CI/CD and containerized deployments, ensure security/compliance, and collaborate with stakeholders to deliver measurable operational improvements.