Top Data Analyst Jobs in Singapore

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.

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.

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.

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.

Summer analysts will build and deploy machine learning, generative AI, and agent-based solutions; integrate complex datasets; develop predictive models; run experiments; analyze trends; and deliver actionable insights. They will also support data governance, risk management, data quality, privacy, and regulatory controls while collaborating with agile, cross-functional teams. The program includes mentorship, training, and potential full-time opportunities after graduation.

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.

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.

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.

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.

The Assistant Data Analyst Manager will lead an analytics team, manage stakeholder relations, oversee Power BI projects, and contribute strategically to data initiatives.

Leads an L2 service recovery team supporting critical banking systems. Oversees major incident resolution, escalations, root cause analysis, service-level adherence, runbooks, post-incident reviews, and continuous improvement. Partners with engineering and infrastructure teams to implement permanent fixes, supports disaster recovery and business continuity activities, ensures regulatory compliance, and maintains 24/7 coverage while developing team capability.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

The Business Analyst will manage product development and support, translating business needs into application requirements, focusing on data management and governance, and working closely with technology teams.

Analyze payment flows and network fees, translate network specifications into billing models, identify cost-saving opportunities, partner with engineering, product, and finance, maintain fee accuracy and alerts, document and scale operational processes, and educate stakeholders.

Support distribution & logistics team with data collection, analysis, and audits. Create templates, work with external partners, benchmark performance, audit freight documentation, assist monthly customs compliance reporting, generate management reports, and support SOP and project implementation.

Manage user acquisition and retention funnels; design, implement, track, and optimize multi-platform acquisition campaigns; own BI and CRM dashboards; measure marketing channel performance; run experiments to improve ROI; work in a small team and take ownership of growth projects.

Own the end-to-end analytics lifecycle: define measurement frameworks, build and maintain data pipelines and dashboards, analyze product/behavioural/model data, support experiment/A-B test design, ensure data quality, and communicate insights to influence product and model decisions.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.