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AdrianGalvanZamora/README.md

Adrián Eduardo Galván Zamora | Data Analyst

🚀 About Me

Hi! I'm Adrián, a Bilingual Data Analyst based in the Mexican Caribbean. I bridge the gap between raw data and business strategy. With a background as a Professional Interpreter, I possess a unique ability to communicate complex insights to stakeholders clearly and effectively.

I specialize in Revenue Optimization, User Behavior Analysis, and Operational Efficiency using the modern data stack.

🛠 Tech Stack

💼 Portfolio: Solving Real Business Problems

🎮 Global Gaming Market Strategy | Predictive Analysis

The Business Problem: An online store needed to identify which video game genres and platforms would drive the most revenue in the upcoming year to optimize their advertising budget.

  • Key Insight: Identified a declining trend in legacy platforms and pinpointed 2 specific genres responsible for 60% of high-margin sales.
  • Tech Stack: Python (Pandas, Scipy for Hypothesis Testing), Matplotlib.

🍔 Food Delivery App | User Conversion Optimization (A/B Testing)

The Business Problem: The UX team wanted to know if changing the fonts would increase user conversion through the sales funnel.

  • Key Insight: Conducted an A/A/B test on 240k+ logs. Proved statistically that the design change had no significant impact on conversion, saving the company from an unnecessary and costly UI overhaul.
  • Tech Stack: Python (Seaborn, Plotly), Statistical Significance Testing.

☎️ Telecom Efficiency Dashboard | Tableau

The Business Problem: A virtual telephony service needed to reduce operational costs by identifying ineffective operators who missed calls or had high wait times.

  • Key Insight: Developed a dynamic dashboard that flagged underperforming agents based on custom KPIs, allowing management to target training resources effectively.
  • Tech Stack: Tableau (Dashboards & Storytelling), Data Cleaning.

🚗 Used Car Price Predictor | Streamlit Web App

The Business Problem: Sellers struggled to price their vehicles competitively without historical data.

  • The Solution: Built an interactive web application that analyzes market trends based on vehicle age, condition, and odometer reading.
  • Tech Stack: Python, Streamlit (Web Deployment), SQL.
🇲🇽 Versión en Español (Click para desplegar)

Sobre mí

¡Hola! Soy Adrián, Analista de Datos Bilingüe. Combino habilidades técnicas con una fuerte capacidad de comunicación (gracias a mi experiencia como intérprete). Me especializo en transformar datos complejos en decisiones de negocio claras.

Proyectos Destacados (Resumen)

  • Estrategia de Mercado de Videojuegos: Modelo predictivo para optimizar presupuesto publicitario identificando géneros de alto rendimiento.
  • Optimización de App de Delivery: Test A/B para validar cambios de UX, evitando gastos innecesarios en rediseños sin impacto.
  • Eficiencia Operativa en Telecom: Dashboard en Tableau para identificar operadores ineficaces y mejorar el ROI del Call Center.
  • Predictor de Precios de Coches: Web App interactiva (Streamlit) para análisis de mercado en tiempo real.

🌐 Let's Connect

I am currently open to remote roles worldwide.

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  1. video_games_sales_analysis_ice video_games_sales_analysis_ice Public

    Exploratory data analysis of historical video game sales to uncover key success factors by platform, genre, and region. Includes hypothesis testing and market insights for strategic marketing decis…

    Jupyter Notebook

  2. user_behavior_food_app_analysis user_behavior_food_app_analysis Public

    Data analysis project examining user behavior within a food delivery app. Includes funnel exploration, A/A/B test evaluation, and hypothesis testing using Python, pandas, and visualization libraries.

    Jupyter Notebook

  3. Predictiv_Analysis_of_Obesity_and_Nutrition_Habits Predictiv_Analysis_of_Obesity_and_Nutrition_Habits Public

    Machine learning project that predicts obesity levels based on eating habits, physical activity, and demographic factors. Includes EDA, hypothesis testing, and a Random Forest classifier with 94% a…

  4. wine-quality-predictor wine-quality-predictor Public

    Predicción de la calidad de vinos tintos con machine learning usando Random Forest y análisis estadístico del dataset Wine Quality.

  5. Forest_Cover_Type_Prediction Forest_Cover_Type_Prediction Public

    Predicting forest cover types using cartographic variables such as elevation, slope, and soil type. Includes EDA, hypothesis testing (ANOVA), and a Random Forest classifier achieving 88.9% accuracy.

  6. Diabetes_Prediction_Model Diabetes_Prediction_Model Public

    Predictive modeling project for early diabetes detection using the Pima Indians dataset. Includes EDA, statistical testing, and Random Forest classification.