Browse top Filipino AI Data Analysts, AI-matched and reviewed by our team. Message them directly on FindTalent. From $5/hr.
An AI Data Analyst uses artificial intelligence tools alongside traditional data analysis techniques to extract insights from structured and unstructured data: using LLM (large language model) tools for natural language querying, AI-assisted data visualization, and automated insight generation. The role combines the SQL and visualization skills of a traditional data analyst with AI tool fluency to accelerate analysis workflows and handle unstructured data sources that conventional analysis cannot process. Filipino AI Data Analysts are emerging from the intersection of the country's strong data analytics talent pool and rapid AI tool adoption. Most have backgrounds in data analysis, business intelligence, or reporting and have integrated tools like ChatGPT Code Interpreter, Google Gemini, or Python-based AI libraries into their workflow. Browse profiles and message directly.
An AI Data Analyst uses AI tools to accelerate data analysis, extract insights from unstructured data, and produce reporting at higher throughput than manual analysis allows. Day-to-day responsibilities typically include:
Filipino AI Data Analysts combine strong Excel and SQL foundations (common in the Philippine business and finance workforce) with active adoption of AI analysis tools. English fluency is important for this role because AI-assisted analysis often involves prompting AI tools in English and producing reports and narrative summaries for English-language stakeholders. Many Filipino data analysts have worked in BPO (business process outsourcing) reporting functions for international clients, producing clear, structured reports under deadline. Shift alignment to client business hours is standard. FindTalent's direct-hire model means no agency markup.
Filipino AI Data Analysts typically charge $9–22/hr compared to US-based data analysts at $35–90/hr, a savings of 70–78% for comparable analysis output. Monthly retainers range from about $1,400 for an analyst producing standard reporting and basic AI-assisted data extraction to $3,500 for a senior AI Data Analyst building automated analysis pipelines, conducting unstructured data analysis, and delivering executive-level business insight reports.
Usual rates per experience level
| Experience | Hourly rate |
|---|---|
| Entry-level | $7–$13$1,200–$2,000/mo |
| Mid-level | $13–$20$2,000–$3,200/mo |
| Senior | $20–$31$3,200–$5,000/mo |
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A traditional data analyst queries structured databases, builds dashboards, and produces reports from well-organized data. An AI Data Analyst does the same but also uses LLM tools to analyze unstructured data (text, surveys, reviews), accelerate exploratory analysis, and generate narrative summaries automatically. The AI layer increases throughput and extends analysis to data sources that SQL alone cannot process. For most SMB (small and medium business) reporting needs, the AI tools add meaningful time savings on top of traditional methods.
Anything you give them access to; the analyst does not have inherent access to your data. Provide database credentials with read-only access to the tables relevant to their analysis, API exports from your SaaS tools, or CSV exports of reports. Establish data access governance before the engagement starts: what data they can access, how it should be handled, and any PII (personally identifiable information) considerations.
Start with the decision you are trying to make, not the metric. 'Which acquisition channel is driving the highest LTV (lifetime value) customers?' is a better starting point than 'build me a dashboard.' Work backward from the decision to the data required. An AI Data Analyst who understands the business question will produce more relevant analysis than one given an open-ended 'analyze our data' instruction.
Provide the minimum data access required for each analysis: read-only database access scoped to specific tables, not full admin credentials. For sensitive datasets (customer PII, financial records), consider anonymizing or masking identifiers before sharing. Use a dedicated data warehouse or analytics environment rather than giving direct access to production databases. Review the analyst's data handling practices at the start of the engagement.
Mae M.
Performs data annotation, labeling image and videos. Accurately tagging 300+ task a day while maintaining high accuracy.
John A.
Designs and builds RAG pipelines, AI agents, and end-to-end automation where data integrity is the design goal: source-cited retrieval, failure-path testing, confidence-gated learning, vector stores kept in sync with source documents. Treats AI builds as production systems, not experiments — tested
Shane C.
Experienced in AI-assisted workflows, business process automation, and operational support, with hands-on experience using Lark Base, Lark Automations, Slack, Google Workspace, and spreadsheets. Skilled in creating automated notifications and workflows, managing databases, improving processes,
Cristian J.
Results-driven Information Technology professional, DataCamp-Certified Data Analyst, and Certified Prompt Engineer specializing in Full Stack Developer workflows, business intelligence, and AI-Automation. Proven capability in building cross-platform web and mobile applications using Flutter, Java,
Von M.
Machine Learning Engineer with a background in Electrical Engineering, Data Analytics, and process optimization, combining engineering expertise with Python, machine learning, data analysis, and AI-driven automation. I specialize in transforming complex data into practical, automated solutions—from
Bill S.
I have AI/data-related experience through BeeMaps, where I worked with map and location-related data, followed task guidelines, reviewed information for accuracy, and performed quality checking. I am comfortable with detail-focused online tasks, reviewing data carefully, following instructions, and
Kristel e.
Dedicated and detail-oriented professional with experience as a Boutique Sales Associate and freelance AI support specialist. Strong background in customer service, sales support, communication, and relationship building combined with hands-on experience in AI data annotation, chatbot training,
Dominic L.
Developed Applications with AI features. Notable once are Real Estate Video Generator, our engine used AI voices, captions and stories for a great video output. Also did chatbots for a business, simple data feed and its Q&A. Booking System thru chatbot, AI response then book.
Joer T.
Designed and developed business automation systems using Google Apps Script and Google Sheets Built lending management systems with automated computations and tracking features Created booking and reservation systems for rental and staycation businesses Developed client management systems with