Top Data Jobs in Singapore

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.

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.

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 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.

Paid full-time internship analyzing large-scale WeChat data to identify product opportunities, build dashboards, design scalable data pipelines, and integrate AI tools (LLMs, RAG, AI agents) to automate analysis and support cross-functional product decisions.

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.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

A 12-month graduate programme offering rotations and hands-on projects in Technology or AI & Data Science. Responsibilities include building and deploying software, cloud and infrastructure work, cybersecurity practices, and developing ML/GenAI solutions (LLMs, agents, MLOps). Participants receive structured training, mentoring, and exposure to senior leaders while working on real enterprise problems to deliver scalable, secure, and impactful solutions.

Lead regional data centre operations to ensure 24x7 uptime and SLA compliance. Oversee Operations Directors and site teams, manage emergency escalations, vendor contracts, audits, compliance (ISO/SOC), budgeting (OPEX/CAPEX), change management, root cause analysis, and operational reporting. Drive operational and financial efficiencies and support strategic planning and stakeholder communications across a Southeast Asia portfolio.

Lead design and delivery of AI-powered automation, Copilot agents, advanced analytics, and monitoring solutions for global Healthcare Compliance. Translate business problems into scalable data-driven solutions, partner with governance and technology teams, and mentor stakeholders while implementing APIs, BI dashboards, process mining, and Cloud-based generative AI capabilities.

Lead APAC Data Quality governance: define framework, standards, KPIs and DQ score; prioritize critical Data Products; translate business needs into testable quality requirements; coordinate IT/delivery partners for monitoring and remediation; enable trusted structured and unstructured content for analytics and Generative AI; influence cross-functional stakeholders and represent APAC in global forums.

Design, train, evaluate and deploy machine learning and AI models. Build data pipelines, preprocess data, run EDA, optimise algorithms, deploy models to production (cloud/APIs/containers), monitor performance, document models, and collaborate with cross-functional teams on AI prototypes and production solutions.

Conduct research on vector search and AI methods for sustainability. Develop quantitative sustainability indicators, AI-enabled monitoring frameworks, and data-driven ESG assessment tools. Build data collection/validation/visualization tools, design experiments and statistical models, ensure trustworthy AI, collaborate with multidisciplinary teams, and produce proposals and scientific publications.

Lead technical design, development, and deployment of data platforms, analytics, and AI solutions. Set architecture, standards, and governance; drive MLOps/DataOps practices, model governance, and integration (including robotics). Provide hands-on delivery, technical direction, and mentorship to ensure scalable, secure, and reusable AI capabilities.

Lead renewable energy and cleantech strategy across APAC, originating and negotiating PPAs and utility agreements. Develop behind-the-meter campus energy solutions (solar, wind, BESS, hydrogen, microgrids), manage grid and utility relations, and drive project delivery from development through commercial operation while aligning energy strategy with growth, sustainability and customer needs.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.

Lead Data & AI engagements across India or Japan: design and deliver data pipelines, analytics, ML and generative-AI solutions; manage client relationships and project delivery; embed model governance, privacy, and explainability; mentor junior staff; and help grow business and localize CFGI accelerators and offerings.

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.

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.

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.

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 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.

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.