<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Isagani Hernandez | Decision-Ready Data Products on Isagani Julian Hernandez III | Data Portfolio</title><link>https://isaganijulian.me/</link><description>Recent content in Isagani Hernandez | Decision-Ready Data Products on Isagani Julian Hernandez III | Data Portfolio</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 03 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://isaganijulian.me/index.xml" rel="self" type="application/rss+xml"/><item><title>InkImpact: Strategic Retention &amp; LTV Intelligence for the Tattoo Removal Parlor</title><link>https://isaganijulian.me/projects/tattoo-removal-parlor-marketing-optimization/</link><pubDate>Wed, 20 Mar 2024 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/tattoo-removal-parlor-marketing-optimization/</guid><description>I built a decision-ready retention analysis that exposed a 43.8% revenue leak, identified high-LTV acquisition channels, and guided budget reallocation toward stronger ROI.</description></item><item><title>Predicting Marketing-Driven Sales</title><link>https://isaganijulian.me/projects/marketing-sales-prediction/</link><pubDate>Sun, 01 Dec 2024 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/marketing-sales-prediction/</guid><description>I built a decision-ready marketing forecasting workflow that used explainable machine learning to predict conversions and clarify which channels were most likely to drive sales.</description></item><item><title>SafeRoute Analytics: A Spatio-Temporal Accident Mitigation Suite</title><link>https://isaganijulian.me/projects/accident-risk-analysis/</link><pubDate>Tue, 15 Jul 2025 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/accident-risk-analysis/</guid><description>I built a decision-ready safety analytics system by engineering 7.7M crash records into risk clusters, severity models, and an interactive advisory tool for logistics and insurance use cases.</description></item><item><title>SkyInsight: Predictive Customer Intelligence for British Airways</title><link>https://isaganijulian.me/projects/skyinsight-ba-analysis/</link><pubDate>Thu, 18 Dec 2025 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/skyinsight-ba-analysis/</guid><description>I built a decision-ready customer intelligence workflow for British Airways that combined NLP and predictive modeling to explain sentiment drivers and forecast booking completion.</description></item><item><title>E-Commerce Pipeline &amp; Market Analytics</title><link>https://isaganijulian.me/projects/ecommerce-analytics/</link><pubDate>Sat, 15 Jun 2024 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/ecommerce-analytics/</guid><description>I built a decision-ready retail analytics pipeline that automated reporting, improved forecasting, and gave a founder-operator cleaner visibility into inventory and demand.</description></item><item><title>Deep Learning RAG Interview Prep Agent</title><link>https://isaganijulian.me/projects/deep-learning-rag-agent/</link><pubDate>Wed, 01 Apr 2026 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/deep-learning-rag-agent/</guid><description>I built the decision-ready retrieval backbone for a deep learning RAG agent, engineering ingestion, vector search, and orchestration so users could get grounded answers with source context.</description></item><item><title>Guardian Recruit: Hybrid Fraud Detection &amp; XAI for Digital Recruitment</title><link>https://isaganijulian.me/projects/guardian-recruit-fraud-detection/</link><pubDate>Sun, 01 Feb 2026 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/guardian-recruit-fraud-detection/</guid><description>I built a decision-ready fraud detection system that combines BERT NLP, anomaly detection, and SHAP explainability to flag suspicious job listings with interpretable risk signals.</description></item><item><title>Lucid ChargeGuard: Strategic Cyber-Risk Mitigation for EV Infrastructure</title><link>https://isaganijulian.me/projects/ev-cyber-attack/</link><pubDate>Thu, 18 Dec 2025 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/projects/ev-cyber-attack/</guid><description>I built a decision-ready cyber-risk analysis for EV infrastructure by using SQL, BigQuery, and Looker Studio to quantify attack exposure and prioritize mitigation.</description></item><item><title>Analytics Pipeline &amp; Live Measurement</title><link>https://isaganijulian.me/analytics/</link><pubDate>Fri, 03 Apr 2026 00:00:00 +0000</pubDate><guid>https://isaganijulian.me/analytics/</guid><description>&lt;h1 id="analytics-pipeline--live-measurement"&gt;Analytics Pipeline &amp;amp; Live Measurement&lt;/h1&gt;
&lt;p&gt;This portfolio is instrumented as a lightweight analytics product, not just a static website.&lt;/p&gt;
&lt;p&gt;The goal is simple: use real visitor behavior to demonstrate how I design measurement plans, structure event data, and turn usage patterns into decision-ready dashboards.&lt;/p&gt;
&lt;h2 id="in-progress"&gt;In Progress&lt;/h2&gt;
&lt;section class="analytics-progress-card"&gt;
 &lt;p class="analytics-kpi-label"&gt;In Progress&lt;/p&gt;
 &lt;h2&gt;Turning live GA4 data into a recruiter-ready dashboard&lt;/h2&gt;
 &lt;p&gt;The measurement layer is now live on the production site and collecting real visitor behavior in GA4. The next phase is building the reporting layer: defining custom dimensions and conversions, connecting GA4 export to BigQuery, and publishing a Looker Studio dashboard that surfaces engagement, project interest, and conversion behavior.&lt;/p&gt;</description></item><item><title>Isagani Julian Hernandez III | Data Portfolio</title><link>https://isaganijulian.me/about/</link><pubDate>Tue, 16 Dec 2025 22:22:28 -0600</pubDate><guid>https://isaganijulian.me/about/</guid><description>&lt;h1 id="i-build-decision-ready-data-products"&gt;I Build Decision-Ready Data Products&lt;/h1&gt;
&lt;p&gt;I am &lt;strong&gt;Isagani Julian Hernandez III&lt;/strong&gt;, an &lt;strong&gt;M.S. Data Science candidate at the University of North Texas&lt;/strong&gt;, graduating &lt;strong&gt;May 2026&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;I position myself as a &lt;strong&gt;business-minded data builder&lt;/strong&gt;: someone who turns messy data into pipelines, models, dashboards, and recommendations that teams can actually use.
My edge is combining analytical rigor with systems thinking so the work does not stop at insight — it becomes a decision-ready product.&lt;/p&gt;</description></item></channel></rss>