Data Analyst

VíctorToret

I turn raw data into stories worth telling — SQL, Python, Power BI.

About me

The analyst behind the data

I'm 36, a data analyst with a backpack full of miles and the conviction that data always has something to tell. I studied Sports Science in Barcelona, worked for years as a personal trainer, and lived in Spain, Colombia, Chicago, Mexico, and spent five months in the Philippines. Each place taught me that behind every business decision—from training loads to restaurant flows to tourism metrics—there are numbers that speak clearly if you know how to listen.

Victor Toret — Data Analyst
Beyond the screen

My World

What I work with

Skills & Certifications

Technical Stack
Languages & Databases
Python SQL MySQL
Analytics & Visualisation
pandas NumPy Scikit-learn XGBoost Power BI Azure Maps Excel
Tools & Other
Git / GitHub Ollama (LLM) GDPR / Privacy tabula-py Faker
Certifications

Data Analytics Bootcamp

Immune Technology Institute · 2025

SQL for Data Science

UC Davis · Coursera

Excel for Data Analysis

IBM · Coursera

Project Management Foundations

Google · Coursera

Data Science & AI Fundamentals

Immune Technology Institute

Languages
SpanishNative CatalanNative EnglishFluent
Portfolio

Featured Projects

01

Philippines Tourism Analysis

End-to-end ETL pipeline on official Philippine tourism data (2015–2023). Automated extraction from annual PDF reports, multi-source cleaning with Python, and Power BI dashboard with Azure Maps.

SQL Python Power BI Azure Maps pandas tabula-py

"Born during a 5-month stay in the Philippines. The data told a story I was living."

View on GitHub
02

NovaShop — Privacy Pipeline

GDPR-compliant data pipeline for a fictional e-commerce. Synthetic data generation with Faker, unstructured PII detection using Ollama (llama3.2), and anonymisation techniques: SHA2 hashing, masking, noise injection, k-anonymity.

MySQL Python Ollama GDPR Faker

"Started as curiosity about anonymising data before sending it to AI. Became a full privacy engineering project."

View on GitHub
03

JoyClinic — Sales Forecasting

Sales forecasting model for a real healthcare clinic using XGBoost. Multi-source merge: bookings, weather, local events, public holidays. Progression: Linear Reg. (R²=0.61) → XGBoost (R²=0.74) → Enriched XGBoost (R²=0.79).

XGBoost scikit-learn Python Power BI pandas

"My first project with real data. Models improve when you understand the business, not just the algorithms."

View on GitHub
Let's talk

Get in touch

If you think we'd be a good fit — drop me a line.