Top Data Analyst Jobs in Singapore

Develops actionable portfolio insights using complex datasets, dashboards, reports, and advanced analytics. Builds and deploys machine learning models, collaborates on predictive and prescriptive analytics projects, and owns initiatives from requirements gathering through deployment. Maintains documentation, improves data quality, and supports analytical data warehouses and tools. Requires strong SQL, R, Python, visualization, communication, and quantitative analysis skills, with Google Cloud and corporate real estate knowledge preferred.

Partner with global teams to drive international expansion through experiments, data pipelines, dashboards, metrics, and actionable insights. Translate business goals into analytical frameworks, collaborate with product and engineering teams, and deliver reporting, recommendations, and self-service tools that improve stakeholder data literacy and support growth decisions.

Analyze financial data and payment flows, assess data quality and reconciliation accuracy, build production tooling and dashboards, automate compliance reporting, analyze costs, and collaborate with engineering, product, and finance stakeholders. Present findings, participate in technical reviews, and communicate project progress while learning unfamiliar systems and solving operational problems.

Build and manage complaints and customer-friction data assets, including sourcing, validation, transformation, data modeling, thematic analysis, monitoring, anomaly detection, dashboards, and management reporting. Identify emerging customer risks, dissatisfaction drivers, and escalation signals through advanced analytics. Partner with stakeholders to improve data quality, customer-outcome oversight, governance, and decision-making while communicating actionable insights to senior leaders.

Audits and validates labeling annotation data for accuracy, consistency, guideline adherence, and regulatory compliance. Identifies errors and root causes, monitors quality KPIs, leads governance cycles, translates data trends into process improvements, and leads the NC Program. Collaborates with agencies and internal stakeholders across labeling operations.

Maintain controlled static and reference data for Treasury platforms and downstream trade-processing activities. Responsibilities include creating and validating records, performing maker-checker controls, investigating exceptions, maintaining audit trails, supporting data-quality reviews, and coordinating with Markets, Operations, Risk, Compliance, Finance, Technology, and external providers. The role also supports projects, testing, process improvements, automation, procedures, training, and business continuity while meeting service levels, operational controls, and regulatory requirements.

Analyze large datasets using SQL and Python, maintain recurring analyses and data products, perform quality checks, investigate discrepancies, and identify trends. Collaborate with Research, Engineering, and Product teams to resolve data issues, document findings, and improve analytical workflows through automation and AI tools. The role is designed for an early-career analyst who is detail-oriented, curious, and interested in using data to inform investment decisions.

Manage and govern the bank’s enterprise Power BI platform, including Microsoft Fabric capacity, workspaces, gateways, access controls, reporting standards, deployment, monitoring, and performance optimization. Lead Power BI development practices, SQL-based data integration, Python automation, Jenkins workflows, and release management. Partner with engineering, infrastructure, security, governance, vendors, and business stakeholders to deliver secure, scalable, compliant analytics solutions while mentoring developers and coordinating concurrent initiatives.

Analyze manufacturing, inventory, and supply chain data; monitor supply risks; support forecasting; review planning parameters and system compliance; present insights; build automated reports and dashboards; use AI tools to improve processes; and contribute to continuous improvement and digital transformation initiatives.

Designs Qlik Sense dashboards, reports, data models, and visualization solutions while building AWS-based data pipelines with Glue, S3, Redshift, and Athena. Partners with stakeholders to translate business needs into BI solutions, implements governance and access controls, manages the Qlik Sense environment, optimizes performance, supports UAT and adoption, and mentors team members. Requires strong SQL, dimensional modeling, data visualization, and BI security experience.

Analyze and visualize data, build complex SQL queries and data pipelines, and operationalize analytics workflows using Python, R, and BI tools. Develop end-to-end data-centric solutions aligned with customer objectives, strengthen problem-solving capabilities, and grow into a subject matter expert. Experience with cloud services, database development, statistical modeling, predictive analytics, machine learning, and analytics platform certifications is advantageous.

Develop and deploy AI, machine learning, GenAI, automation, and analytics solutions for Group Risk Management. Partner with business, technology, data engineering, and data science stakeholders to define requirements, deliver use cases, and influence decisions. Guide teams on model selection, GenAI cost estimation, benefit realization, governance, privacy, and responsible AI. Maintain existing solutions, promote AI adoption, and oversee analytics work across risk departments.

Analyze customer and payment-message screening performance across DBS operating countries. Develop and backtest recommendations for detection rules, matching logic, thresholds, and risk scoring; evaluate risk coverage, false positives, data quality, and operational efficiency. Translate findings into requirements and test scenarios, support UAT and implementation validation, provide regulatory and audit evidence, and advise Compliance, Technology, Operations, and business stakeholders as a screening analytics subject matter expert.

Analyze e-commerce data across Reolink’s official website and Amazon platforms to generate insights, improve profitability and performance, and support product decisions. Build data pipelines, dashboards, APIs, and e-commerce metrics systems; validate data quality, investigate issues, and collaborate with product management, engineering, design, and data engineering teams to drive data-informed growth.

Analyzes international trade, tariff, customs, shipment, and trade agreement data; prepares reports and recommendations on risks, costs, duty optimization, and trade strategy. Monitors import/export compliance across China, Europe, and Asia, maintains SAP/MIC trade data, resolves discrepancies, supports customs reconciliation, researches regulatory changes, and identifies automation and process improvement opportunities. Collaborates with logistics, supply chain, finance, legal, compliance, and regional trade teams.

Supports the IT PMO by maintaining Power BI dashboards, validating data, analyzing project portfolio trends, and translating findings into management insights. The role improves PMO reporting processes, collaborates on dashboard requirements, and manages the PMO homepage and communications mailbox. It requires strong analytical, communication, organizational, and process-improvement skills, with experience in business intelligence, project reporting, or PMO support.

Leads functional business analysis for enterprise compliance technology initiatives covering KYC, AML, sanctions, anti-bribery, and fraud workflows. The role defines business and technical requirements, target processes, roadmaps, testing strategies, scope changes, governance, and deployment plans. It manages senior stakeholders, risks, funding alignment, and post-go-live knowledge transfer while leading and developing a team of functional business analysts.

Supports AI and data governance by managing model access, auditing permissions and compliance processes, documenting governance activities, monitoring models, developing awareness training, tracking regulatory trends, and preparing governance reports. Collaborates with IT and business teams to ensure AI and data models follow security protocols, data protection laws, and internal policies.

Lead AML data science and analytics initiatives: perform strategic data analysis, statistical modeling on large datasets, consult with business stakeholders, drive system changes from requirements to implementation, improve data quality, and mentor junior staff while managing risk and compliance.

Connects marine, data, and delivery teams by integrating and validating shipping data, analyzing large datasets with SQL, translating business needs into technical requirements, and coordinating Agile delivery. Applies marine and dry bulk shipping expertise across vessels, voyages, ports, cargoes, bunkers, and operations while supporting predictive analytics, data quality, stakeholder management, testing, and implementation.

Supports distribution and logistics analytics by maintaining material master data, assisting with month-end accruals, cleansing freight-spend data, and enhancing Excel reports with Python. Builds dashboards comparing volume, budgets, forecasts, and actuals, publishes reports in Power BI, investigates outliers, coordinates with internal and external providers, and updates user documentation.

Own pricing and retail analytics initiatives, including decision systems, reports, metrics, statistical analysis, and business insights. Lead end-to-end projects, translate complex data for stakeholders, influence product and strategy decisions, and collaborate with Pricing, Retail Commerce, 3P Commerce, Promotions, developers, and analysts. Ensure data quality, improve reporting systems, solve ambiguous problems, and provide strategic guidance in a fast-paced e-commerce environment.

Leads advanced data analysis projects using statistical models and predictive techniques to solve complex business problems. Develops dashboards, visualizations, insights, and recommendations for senior stakeholders while partnering with business leaders on data-driven improvements. Mentors junior analysts and independently manages high-visibility analytics initiatives.

Build and maintain dashboards tracking activation, retention, task success, and agent reliability; analyze agent run data to locate failures and stalls; design instrumentation and metrics; support experiment design and readouts; produce reproducible analyses and actionable recommendations for product and engineering.

Lead partner-focused analytics for APAC: investigate conversion, churn, and payment-funnel issues; analyse large operational datasets; build dashboards and automated reports; perform root-cause analysis; collaborate with commercial teams and external partners; apply analytics engineering and emerging AI tools to improve partner outcomes.