Top Data Analyst Jobs in Caloocan

The Data Analyst will act as a subject matter expert in data engineering, healthcare risk adjustment, and application analysis, focusing on reliable data solutions and troubleshooting workflows.

Analyze complex datasets to provide insights, develop Sales Pipeline reports from Oracle Sales Cloud, build dashboards and PowerApps automations, perform descriptive and predictive analytics, support market research, and contribute to continuous process improvements and administrative tasks.

Prepare and reconcile monthly private investment reports, analyze investment exposure versus targets, and consolidate data from multiple internal and external sources. Perform detailed reconciliations of portfolio data (spreads, balances, commitments) and apply advanced financial analysis and Excel/Power BI skills to support the private credit team.

Register samples into LIMS, create work orders, apply QC protocols, generate acknowledgements, link pricing, produce and distribute invoices/statements, follow up on payments, and maintain accurate reports and databases while supporting ad hoc projects and complying with company policies.

The Data Analyst will transform data into insights, develop reporting solutions, maintain data accuracy, and collaborate with stakeholders to drive efficiency.

Produce real-time cricket insights and pricing using expert cricket knowledge and existing models. Analyze pricing data, run live simulations, validate outcomes, support clients, and provide high-quality data-driven insights.

Support portfolio management through data collection, entry, analysis, dashboarding, and reporting using Clarity PPM and analytics tools. Maintain systems, produce visualizations and trend analysis (Power BI, Excel), resolve user requests, and recommend process improvements to improve portfolio transparency and outcomes.

Perform sample registration, administrative data entry, billing support, and report preparation using LIMS/CRM. Ensure data quality, meet lab deadlines, support sales and respond to technical queries while following SGS QA and safety policies.

Lead end-to-end analytics initiatives: perform ETL/ELT, automate data pipelines, develop dashboards and predictive models, ensure data quality and governance, validate models, and present insights to business and executive stakeholders.

Seeking a detail-oriented DBA/Data Analyst to analyze datasets using Python and SQL, creating dashboards, and presenting insights to aid decision-making.

The Risk Data Analyst will extract, validate, and maintain risk datasets, manage reporting, develop dashboards, and monitor risk metrics to support risk management teams.

Register samples into LIMS and create accurate work orders, apply QC protocols, link pricing, generate acknowledgements, invoices and statements, distribute to clients, follow up on payments, maintain reports and databases, and support ad hoc projects.

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

Lead integration of AI, automation, and digital tools into HSW processes. Own HSW data strategy, governance, and roadmap. Deploy and manage Cority, AI/ML tools, Power BI dashboards, and cloud analytics to deliver insights, predictive models, and improved safety outcomes. Partner cross-functionally to ensure ethical, secure, and compliant deployment, drive adoption, and measure impact.

The Data Analyst extracts and analyzes data from Oracle, produces reports, and assists in tracking key performance indicators related to kit and spares shipments.

Consult with stakeholders to define questions, prepare and clean large datasets, run intermediate statistical analyses, build visualizations (Tableau/Power BI), lead small analytics projects, and communicate actionable insights. Uses SQL/Python and basic big-data tools; promotes analytics best practices and leverages approved AI tools to accelerate workflows.

Collect, cleanse, and analyze client data; build automated file-processing and reporting workflows; run SQL queries and create Python or Power BI reports; enforce data quality; collaborate with analytics teams and stakeholders to deliver actionable insights.

Manage compliance for defined contribution retirement plans: perform non-discrimination testing, census reconciliation, contribution/forfeiture allocations, Form 5500 filings, data analysis, and respond to auditors and plan representatives. Support account management, process improvement, and team training.

Lead complex analytics for global complaint vigilance: perform trend and risk analyses, build dashboards, support data ingestion and data-lake strategy, present findings to QA and cross-functional partners, and enable corrective action and regulatory responses.

Monitor and record shipment statuses during a fixed night shift, update and complete shipment records in the CRM via call verification with delivery providers, clear statuses, and escalate issues or incomplete records to the client.

Analyze and visualize post‑market surveillance and complaint data to support investigations, regulatory reporting, trending, and CAPA. Create reports and metrics, apply statistical techniques, ensure data integrity, recommend process improvements, and participate in audits and inspection readiness activities.

The Data Analyst/Data Enrichment Specialist manages and maintains data integrity across platforms, builds targeted lists, handles event registrations, and supports marketing initiatives.

Design, develop, and maintain interactive Tableau dashboards; gather stakeholder requirements; optimize SQL queries and data models; ensure data accuracy; produce reports and provide dashboard support and troubleshooting.

The Data Analyst will design and maintain dashboards using Tableau and Power BI, analyze data for insights, and support PMO initiatives. Collaboration with leadership and ensuring data quality are key responsibilities.

The Finance Data Analyst gathers, cleans, and analyzes financial data, prepares reports, supports month-end reporting, and aids in financial modeling to enhance efficiency.