Top Data Jobs in Singapore

Prepare month-end closes, forecasts, variance analysis, account reconciliations and profitability reviews. Provide insights and recommendations, support budgeting, analyze project and departmental costs, and identify cost-management opportunities for international operations.

As a Data Engineer, you will build and maintain data systems for drug safety AI tools, ensuring reliable data processing and storage for research teams.

Remote annotator reviews Japanese text and images, draws bounding boxes, answers structured questions, and writes short summaries per guidelines to train AI systems. On-the-job training provided; assessment required.

Design, build, and maintain data models, ETL pipelines, dashboards, and APIs to support industry models, research, and consulting. Ensure data accuracy, completeness, and observability while integrating new datasets and cloud infrastructure. Collaborate with analysts and stakeholders to deliver robust, modular production data systems with minimal supervision.

Develop and implement statistical models for data analysis, collaborate with teams for process improvement, and present findings to management. Stay updated on data science and machine learning advancements.

As a Data Analyst at Manus, you'll analyze business metrics and user behavior, conduct A/B tests, and create dashboards to drive product strategy and growth.

Design and deliver production-ready AI and data science solutions across CRM, retail, marketing and operations. Build ML models, GenAI/RAG pipelines, feature engineering and training workflows; collaborate with data engineering to deploy, monitor and optimize models; run experiments and measure business impact while ensuring responsible AI, security and governance.

Lead lifecycle management of divisional and functional data products (dashboards, reports, datasets, future AI products). Facilitate data stewardship, define critical data elements and quality rules, prioritize product backlog, coordinate BI/data engineering delivery, and drive adoption and continuous improvement to ensure trusted, fit-for-purpose data and actionable insights.

Lead identification, framing and orchestration of high-value data and AI initiatives across the region. Define strategic KPIs, build business cases, prioritize use cases, and translate approved initiatives into delivery and adoption plans. Drive product adoption, change management, upskilling and measurement of business impact; liaise with Finance, HR/P&O, President Office, tech and data teams to ensure alignment, readiness and sustained value realization.

Lead SEAA's regional Data & Intelligence strategy, prioritize and deliver data, analytics and AI initiatives, guide platform and architecture choices, embed governance and responsible AI, drive data literacy and adoption, and build a high-performing data team aligned with global standards.

Lead design and operation of scalable data ingestion pipelines, curated datasets and semantic models. Partner with Data Product, Stewardship, Analytics and Data Science to deliver governed, high-quality data foundations. Build and optimize Power BI dashboards, enforce data quality and lineage, and enable AI-ready datasets to support reporting, analytics and AI-enabled products.

Lead and support analytics lifecycle activities: manage analytic data platforms, govern data access, design and implement reporting/BI, apply advanced quantitative modeling, deliver actionable business insights, contribute to policies, work independently on complex projects and mentor junior colleagues.

Lead design, transformation, and operationalization of enterprise hybrid cloud environments. Produce high- and low-level designs, migration roadmaps, runbooks, and Day-2 operational models. Hands-on across on-premises and public cloud platforms, ensuring connectivity, security, identity, backup, monitoring, automation, and cost governance. Engage clients, support proposals and commercial models, mentor teams, and ensure smooth transition to managed services with strong SLAs, observability, and operational resilience.

Coordinate and support end-to-end delivery of telecommunications, P2P connectivity, and cloud projects. Monitor progress, manage risks, engage vendors and cloud providers, maintain documentation, track billing milestones, and ensure customer-centric handover. Provide network troubleshooting, use monitoring tools, and pursue relevant certifications to strengthen networking skills.

The Senior Data Scientist will build and manage the intelligence layer of the Railway Common Data Platform, implement machine learning solutions, and enhance operational efficiency through data analytics and AI capabilities.

Analyze operational, financial, maintenance, and resident feedback data to identify trends and service gaps. Develop and maintain dashboards and KPIs, automate reporting, improve data governance, and provide actionable insights to operations and management. Prepare presentations and support ad-hoc studies to inform strategic planning and enhance resident experience.

Lead NTT DATA's relationship and P&L for strategic Financial Services accounts. Develop and execute client account plans, drive cross-practice sales, grow revenue and margin, manage global partner relationships, reduce churn, and align stakeholders to a unified vision.

Lead development and deployment of Generative AI solutions for underwriting using OpenAI services. Collaborate with engineers and stakeholders to prepare large datasets, build advanced ML models, standardize best practices, and scale AI solutions globally while communicating results to technical and non-technical partners.

Design, build, and maintain scalable ETL/ELT pipelines using Informatica IDMC, PowerCenter, and dbt. Support BI, analytics, and reporting by implementing ingestion, transformation, and loading processes, ensuring data quality. Perform data modeling, schema design, performance tuning on Redshift, PostgreSQL, and Oracle, and lead cloud migration initiatives.

Work on large-scale data: analyze datasets, build dashboards and scalable data pipelines, collaborate cross-functionally, and apply AI tools (LLMs, RAG, agents) to automate analysis and surface product insights. Complete a mentored, data-driven internship project and support operational and security analytics.

Analyze large-scale datasets to identify opportunities and optimize product performance; build dashboards and visualization tools; assist in developing scalable data pipelines to support operations and platform security; and collaborate with product, engineering, and legal teams to turn analyses into actionable business strategies.

Work on data-driven projects to improve WeChat safety strategies: analyze large datasets, build dashboards and visualizations, develop scalable data pipelines to support operations and platform security, and collaborate with product, engineering, and legal teams to turn analytics into actionable strategies.

Lead and deliver multiple concurrent projects or programs from concept to implementation across geographies and technologies. Manage stakeholders, budgets, scope, change control, risks, issues and escalations. Act as primary client contact, ensure quality and satisfaction, coordinate teams, and support pre-sales and proposals when required.

The intern will support AI & Data projects by analyzing data, developing machine learning models, and assisting with data visualization and preprocessing.

The Data Strategy & Analytics Manager drives digital growth through analytics in marketing, campaign performance, and customer journey optimization. They lead data initiatives to enhance acquisition effectiveness, support strategic decision-making, and optimize user experiences, overseeing collaboration across various teams.