Top Data Analyst Jobs in the Philippines

Analyze healthcare risk adjustment and health plan data across Medicare, Medicaid, and ACA Commercial programs. Build and maintain reliable data solutions using SQL, Python, ETL processes, databases, Tableau, Power BI, and Excel. Investigate application, data, system, and workflow issues, identify root causes, recommend corrective actions, and collaborate with technical teams to resolve problems.

Analyze and improve AI-powered transaction monitoring systems for money laundering, fraud, sanctions, and terrorist financing detection. Review high-risk transactions, identify behavioral patterns, test and refine machine learning models, develop metrics and dashboards, conduct experiments and ad hoc analyses, and provide clear recommendations. Collaborate with compliance, legal, Identity & Trust, and operations teams while ensuring AML and sanctions regulatory adherence and a positive customer experience.

The Data Analyst Level I supports data-driven solutions, generates reports using SQL and Excel, and collaborates on client performance analysis.

Manage four or more REPH DRV projects, ensuring quality, SLA compliance, and timely completion. Serve as a subject matter expert on two projects, collaborate with product managers and relevant teams, support junior team members, and identify process improvements. The role requires advanced Excel and MBSI proficiency, Power BI knowledge, and the ability to apply enterprise AI tools to technical workflows and business objectives.

Monitors and analyzes workers’ compensation exposure, claims, and regulatory data. Creates documentation, reports, and statistical data call submissions; investigates data anomalies, bureau criticisms, and external inquiries. Supports surcharge and assessment obligations, resolves data quality issues, fulfills recurring and ad hoc analysis requests, and advises staff and management on process improvements.

Collects, composes, validates, and distributes financial instrument market and master data under client SLAs. Resolves client data questions and service incidents, performs quality checks and analysis, supports operational risk and governance controls, monitors data-supply-chain issues, and contributes to process improvements. The role also documents procedures, supports client-specific requirements, exchanges knowledge across Data Operations teams, and coaches colleagues.

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.

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 cricket statistics, pricing data, and predictive model outputs to support pre-match and live event management. Generate accurate pricing, identify trends and anomalies, maintain simulated matches, validate data outcomes, and provide timely product support to global clients and internal teams. The role requires deep cricket expertise, strong mathematics and analytical thinking, Excel proficiency, clear communication, and the ability to work accurately under pressure.

Analyze cricket statistics, pricing data, and predictive model outputs to support pre-match and live event management. Produce accurate real-time insights, identify trends and anomalies, maintain simulated matches, validate data outcomes, and assist global clients and internal teams. The role requires deep cricket expertise, strong mathematics and analytical thinking, Excel proficiency, and the ability to work accurately under time pressure.

Analyze paid media and broader marketing performance across Meta, Google, YouTube, LinkedIn, and TikTok. Build and automate recurring reports and dashboards using HubSpot, Google Analytics, Data Studio, and spreadsheets. Monitor trends, anomalies, and optimization opportunities; maintain data integrity; support campaign planning and forecasting; and translate complex findings into actionable recommendations for non-technical stakeholders.

Supports portfolio management through data collection, entry, analysis, dashboards, reporting, and recommendations. Maintains Clarity PPM data and responds to user requests, develops databases and data systems, identifies trends, visualizes performance, and recommends process improvements. Collaborates with stakeholders to understand business requirements and presents findings to management using Power BI, Excel, and related tools.

Develops and sustains data reporting, analytics, dashboards, and databases to support continuous improvement and leadership decision-making. Collects, cleans, transforms, and analyzes data; identifies trends, correlations, process improvement opportunities, and data-quality issues. Builds visual reports using Power BI and related tools, presents findings to management, and collaborates with stakeholders to understand business requirements. Requires expertise in data mining, database management, statistical analysis, visualization, and process efficiency.

Own payments and mobile analytics across debit, credit, cross-border, and transaction feeds. Define and validate tracking, analyze funnels and user behavior, build dashboards and self-service reporting, monitor payment metrics, support forecasting and financial reporting, and present actionable insights to stakeholders.

Own and maintain the credit card NPV and unit economics model. Build production-ready Python and SQL logic, create datasets covering cohorts, cashflows, losses, funding, fees, and revenue, automate scenario analyses, validate model outputs against portfolio performance, investigate variances, and document implementation-ready specifications.

Monitors and analyzes Workers Compensation exposure, claims, and regulatory data to improve data quality and support statutory reporting. Creates documentation, reports, and data submissions; resolves bureau criticisms, medical and indemnity data inquiries, and systemic anomalies. Supports surcharge and assessment payments, responds to ad hoc requests, and collaborates with business units and support teams to meet deadlines and regulatory obligations.

Performs laboratory sample registration, data entry, record cleanup, report preparation, billing support, CRM maintenance, quotations, and data-quality verification. Uses LIMS and database systems to manage accurate laboratory reports, meets turnaround deadlines, responds to technical queries, supports operational improvements, and follows SGS quality, integrity, QHSE, and HR procedures. The role is hybrid but may require onsite work for two to six months.

Turn customer, product usage, CRM and operational data into actionable insights to improve retention, engagement and product decisions. Build and maintain reports and Power BI dashboards, perform SQL/Python data extraction and automation, support predictive analytics and AI-readiness, validate data quality, and present clear recommendations to cross-functional stakeholders.

Analyze advertising, market, social media, and enquiry-generation data to identify trends, measure ROI, and recommend marketing decisions. Build dashboards and management reports, maintain data quality across CRM and advertising platforms, manage online adverts and social campaigns, support tenant communications, track budgets, and contribute to events, branding, and office setup. Present insights clearly to technical and non-technical stakeholders.

Develops and maintains efficient dashboards, reports, and visualizations for business and technical audiences. The role transforms, integrates, and federates data; improves data accessibility; maintains reporting documentation; and collaborates with stakeholders across business insights, data engineering, operations, and support. Requires hands-on SQL, Python, and Power BI experience, analytical problem-solving skills, and familiarity with ETL and data warehouses.

Investigate high-risk fraud alerts and complex cases using SQL and transactional, customer, device, and behavioral data. Identify fraud patterns and typologies, evaluate detection rules, recommend controls, and conduct root cause analysis. Build dashboards, reports, and performance metrics for management, operations, compliance, and regulatory use. Collaborate with Fraud Operations, Risk, Product, Engineering, and Compliance to strengthen fraud prevention and analytics capabilities.

Manages customer account, security, pricing, and reference data across multiple systems and teams. Monitors data quality, identifies process improvements, supports client service levels, and contributes to project delivery. Provides team guidance, supervises junior staff, evaluates performance, identifies training needs, and acts as manager backup. Ensures risk management, regulatory compliance, policy adherence, and transparent escalation of control issues within a global financial services environment.

Develops business intelligence solutions for the Sales organization by translating stakeholder needs into SQL-based data models, dashboards, visualizations, and actionable analysis. Builds and maintains a Snowflake data warehouse, establishes SQL and modeling standards, reviews work, leads ambiguous requests, uses AI tools responsibly, trains users, and presents findings to technical and non-technical stakeholders across Finance, Operations, Sales, Content, and IT.

Analyzes and visualizes post-market surveillance and quality-system data to support complaint handling, investigations, CAPA, regulatory reporting, audits, and inspection readiness. The role prepares reports and regulatory content, applies statistical techniques, identifies product quality trends, and recommends process improvements while partnering with Post-Market Quality and cross-functional stakeholders.

Manages investment data quality and governance by setting up securities, investigating discrepancies, validating security master data, maintaining governance processes, and supporting reporting through data extraction, cleansing, transformation, and analysis. The role requires investment operations knowledge, Excel and SQL proficiency, and collaboration across teams to improve data integrity, reporting, and operational processes.