Top Data Analyst Jobs in Singapore

Implement and maintain data governance frameworks, policies, standards, and data quality controls. Support data ownership, stewardship, metadata management, lineage, regulatory compliance, governance forums, stakeholder engagement, training, audits, and enterprise data transformation initiatives for banking clients.

Support investment teams by acquiring, cleaning, and analyzing diverse datasets to test investment theses. Learn fundamental investor approaches, identify key data drivers and inflection points, and present research findings. Work with existing and new data to generate insights and decision-support tools for sector-focused investment research.

Leads cross-functional special projects involving air network planning, scheduling, airline partner performance, and operational analytics. Develops optimization models, analytical frameworks, automation tools, scripts, and lightweight products to improve routing, capacity allocation, scheduling efficiency, and planning workflows. Partners with engineers, operations teams, and management to implement solutions, establish best practices, and scale innovative approaches across the organization.

Manage and maintain material master data in SAP, Syndigo, and related systems across the product lifecycle. Process new material creation, changes, pricing, vendor updates, phase-outs, purchasing records, and intercompany data. Coordinate product catalogue publication, data quality reporting, dashboards, customer data integrations, ticket resolution, governance, SOPs, and process improvements across ANZ stakeholders.

Lead business analysis for an AI and data transformation initiative in banking. Define and improve data enablement processes, translate business and technical requirements, support reusable data products, and address data discovery, governance, quality, lineage, and risk. Coordinate business, data, AI/ML, technology, and risk stakeholders while managing scope, priorities, dependencies, timelines, and delivery blockers. Senior hires lead complex workstreams and contribute to target-state roadmaps.

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.

Entry-level Product Data Analyst internship supporting product analytics: build and analyze conversion funnels, evaluate A/B tests, create dashboards, respond to ad-hoc data requests, write SQL pipelines, monitor data quality, and translate findings into visual summaries to inform product decisions.

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.

Analyze and reconcile financial data, investigate discrepancies, trace data origins, and automate manual validation checks using SQL and Python. Build and maintain Finance dashboards, document datasets, and make missing or inconsistent data visible. The role involves production data, reporting pipelines, version control, review processes, and clear communication of findings. No professional experience is required, but candidates should be numerate, detail-oriented, comfortable questioning data, and able to explain technical discrepancies clearly.

Internship data analyst supporting dashboard monitoring, user behavior and content ecosystem analysis, A/B test evaluation, campaign performance analysis, data quality assurance, and metric documentation. The role uses SQL and Excel to derive insights on engagement, retention, conversion, and creator ecosystems, while collaborating with product and operations teams in a blockchain and digital assets environment.

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.

Analyze sales channels, business performance, revenue, and acquisition trends; build dashboards and reports; design and calculate sales incentive programs; monitor targets; identify optimization opportunities; and present actionable insights to Sales, HR, and other stakeholders. The role requires cross-functional collaboration, banking industry knowledge, and proficiency in analytics, programming, visualization, and reporting tools.

Supports technology-enabled transformation projects for energy and commodities trading clients. Responsibilities include designing operating models and workflows, shaping technology strategies and platform roadmaps, strengthening data and analytics foundations, selecting and implementing CTRM/ETRM systems, applying automation and AI, and developing risk and control frameworks. The role also supports project planning, deliverables, stakeholder relationships, and business development activities.

Analyze global logistics, spend, invoice, and operational data to identify cost drivers, trends, anomalies, and optimization opportunities. Develop and maintain Tableau dashboards, automate reporting, support cost-to-serve models, and contribute to process mining and business intelligence initiatives using tools such as Celonis, Databricks, SAP, and Tableau. Collaborate with logistics teams worldwide, translate business requirements into analytics solutions, and present actionable findings to stakeholders.

Analyze and profile customer, KYC, onboarding, and reference data; design source-to-target mappings; define migration rules and validation criteria; identify data quality issues and anomalies; validate ETL pipelines; perform UAT, mock migration testing, reconciliation, and data verification; prepare technical documentation; and collaborate with business, compliance, governance, operations, and technology stakeholders to resolve migration issues.

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.

Own logistics analytics problems end to end, delivering insights and advanced analytical solutions for fleet sizing, routing, staffing, demand planning, and operational optimization. Apply simulation, optimization, statistical modeling, causal inference, and experimentation methods. Build scalable data products, collaborate with engineering and data teams, mentor junior analysts, and communicate recommendations to senior stakeholders.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Partner with APAC Compliance teams to deliver regulatory reporting, compliance monitoring, risk analytics, and assurance reporting. Build scalable data models, dashboards, and self-service analytics tools while validating regulatory submissions and supporting automated monitoring. Maintain data quality, governance, and documentation, and collaborate with Risk, Compliance, Product, and Engineering stakeholders. The role requires strong SQL and data modeling skills, with opportunities to use dbt, modern data warehouses, data engineering tools, and Python.

Design and deploy AI, automation, data integration, and web application solutions across APAC. Responsibilities include building ETL pipelines, developing AI and machine learning models, creating Power Platform solutions, maintaining applications, gathering requirements, supporting project delivery, and ensuring data and AI governance. The role also involves stakeholder collaboration, presentations, training, troubleshooting, and continuous process improvement.

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.