HR professional with 7+ years of combined experience in HR, data management, and reporting in high-accountability environments — bringing together deep people expertise and a Canadian Graduate Certificate in Data Analytics to drive smarter organizational decisions.
HR & Data Analytics · Windsor, ON · Canada
About me
I began my career as a Military Officer in the Chilean Army, where I spent over five years leading HR and personnel management operations in demanding, high-accountability environments. That experience shaped my ability to manage complex human systems, make decisions under pressure, and communicate clearly across all levels of an organization.
In 2023, I relocated to Canada and made a deliberate pivot into data: first completing a year of Computer Science at the University of Windsor, then completing the Data Analytics for Business graduate certificate at St. Clair College with Academic Distinction.
I bring a rare combination: the discipline and people expertise of a military HR background, and the technical foundation of modern data analytics.
Expertise
Projects
Two-semester industry capstone (5-person team) analyzing user engagement and retention for HALIGHT, a local company in Tecumseh, Ontario. Extracted data from AWS Athena, built Power BI dashboards for attrition, cohort, and what-if analysis, and applied K-Means clustering, logistic regression, and seasonal forecasting to classify engagement and project 2026 trends.
End-to-end churn analysis of an e-commerce customer base. Identified characteristics of churned customers, applied classification models, and developed data-driven retention strategies to reduce attrition.
Exploratory analysis of 3,333 e-commerce customers to identify behaviors linked to churn. Found that customers with push notifications enabled churn at nearly twice the rate (16.7% vs 8.7%), pointing to notification fatigue, and that saved-card users churn at 42%. Translated findings into retention recommendations on notifications, trust, and customer service.
CLV analysis of 10,000 e-commerce customers. Used RFM scoring to identify the top 5% highest-value customers, explored churn and loyalty patterns, and compared regression models (Ridge, Decision Tree, Random Forest, XGBoost, Gradient Boosting) to predict lifetime value.
Analysis of 540K+ retail transactions across 35 countries. Combined RFM analysis with K-Means clustering to identify three customer groups, applied Apriori market basket analysis to find products bought together, and used Pareto analysis to show that 20% of products drive 80% of revenue.
Sentiment classification of 14,640 airline customer tweets. Used word clouds to surface key pain points (delays, cancellations, baggage) and compared Logistic Regression, Random Forest, and SVM with Count and TF-IDF vectorizers; the best model reached 78.9% accuracy.
Comprehensive sales analysis identifying top-performing product categories (Cross Country Race, Over Mountain, Elite Road) and regional market trends across U.S. states from 2011–2015. Focused on profitability drivers and inventory recommendations.
Designed and deployed an electronic survey on AI tool usage and perception (34 respondents). Analyzed results and built a full Power BI dashboard covering usage frequency, device preferences, privacy concerns, and demographic breakdowns.
Multi-tab Streamlit dashboard covering CAPM, WACC, and DCF valuation models. Incorporated Monte Carlo simulation and technical indicators (SMA, EMA, RSI, MACD) across a portfolio of eight companies.
Comparative market analysis of Airbnb listings across Toronto and Vancouver. Applied segmentation and sentiment analysis to uncover pricing trends, demand patterns, and strategic opportunities.
SQL-based exploratory analysis of de-identified ICU patient records from the MIMIC-III clinical database on Google BigQuery. Investigated demographics, mortality patterns (~34% rate), and ICU stay characteristics. Findings support resource allocation and risk stratification decisions.
Quantitative research study (team of 3) comparing how 44 parents/caregivers rate their own parenting style with how their adolescent children perceive it. Applied the validated ESPA29 psychometric scale, analyzed data in SPSS with chi-square tests and ANOVA, and found low agreement between self-perception and the children's perception, consistent with social desirability bias. Approved by the university's research ethics committee. Conducted and presented in Spanish at Santo Tomás University, Chile.
Bilingual Progressive Web App for shared household finance management, built around a real biweekly payday cycle. Tracks income, expenses, recurring bills, and custom reminders. Features a React 19 frontend with Recharts visualizations, a Flask REST API, and a daily cron job for recurring item generation and push notifications via VAPID. Installable on iOS and Android. Developed with Claude (Anthropic) as AI pair-programmer.
End-to-end web application for a nonprofit organization, deployed in production with real users. Includes real-time messaging (WebSockets), push notifications (VAPID), ministry scheduling with role-based access, multilingual support (ES/EN), announcements with PDF viewer, password recovery via email API, and a daily Bible verse feed. Installable as a native app on iOS and Android. Developed in collaboration with Claude (Anthropic) as AI pair-programmer.
Full-stack web application built with Flask and SQLite to explore student wellness metrics — stress level, sleep quality, physical activity, mood, and health risk indicators — across a dataset of 1,000 student records. Started as a group course assignment and extended into a portfolio project: a filterable data table, an interactive dashboard with 8 Plotly charts, an insights page with data-driven recommendations, and a Random Forest risk predictor that takes a student profile as input.
Google Sheets add-on built with Apps Script that auto-generates weekly role assignment schedules across two independent rotation queues (14 participants total), with a sidebar UI for managing availability, replacements, and cancellations — no server required. Uses a priority-counter algorithm to keep rotations fair, and shifts queues automatically when a slot is cancelled. Developed with Claude (Anthropic) as AI pair-programmer.
Education & Background
St. Clair College · Windsor, Ontario
SQL, Python, Power BI, statistical modeling, machine learning fundamentals, and business intelligence.
University of Windsor · Ontario
Completed foundational coursework in programming and computational thinking before transitioning to Data Analytics to better align with HR and business intelligence career goals.
Psychological Care Center · Santiago, Chile
Maintained confidential client databases and accurate records, supporting weekly reviews of 50+ active cases under strict standards for privacy and data integrity. Organized and consolidated information for administrative and clinical reporting.
Santo Tomás University · Santiago, Chile
Specialization in organizational behavior, research methodology, and psychometrics. Credential assessed and recognized by WES as equivalent to a Canadian bachelor's and master's degree.
Chilean Army · Santiago, Chile
Led human resources operations in high-accountability military environments. Managed personnel administration, compliance, workforce planning, and organizational processes across complex institutional structures.
Bernardo O'Higgins University · Santiago, Chile
80-hour specialized diploma in human resources management, complementing active military service with formal academic training in HR practices, personnel administration, and organizational development.
Diego Portales University · Santiago, Chile
Foundational studies in social sciences, research methodology, and human behavior — providing the academic base for later specializations in organizational psychology and HR management.
Certifications
Contact
Open to Data Analyst, Business Analyst, HR Analyst, People Analytics, and HR Generalist roles — in Windsor–Essex or remote within Canada. Authorized to work in Canada.