Pedro Fabián Gutiérrez Vidrio

🎯 I help businesses increase revenue by transforming raw data into actionable insights

Specialized in customer behavior analysis, predictive modeling, and performance optimization that drive strategic decisions and measurable business growth.

PROVEN BUSINESS IMPACT DELIVERED

+18%

Cross-sales increase through A/B Testing optimization

+15%

Model accuracy improvement in customer retention

99.8%

System uptime during critical electoral infrastructure

+40%

Knowledge transfer improvement through documentation

-25%

Technical incidents reduction via preventive maintenance

+22%

User engagement increase through automated reports

-35%

Analysis time reduction through AI-assisted EDA processes

100%

Stakeholder satisfaction through clear data storytelling

Professional Profile

💼 PROVEN IMPACT: Delivered 18% sales increase through A/B testing and 15% improvement in customer retention modeling for real business clients.

🎯 UNIQUE VALUE: Rare combination of PhD-level research skills + hands-on Python/SQL expertise + business intelligence acumen.

Professional in Data Research and Analysis with background in social sciences and professional experience in IT systems. Specialist in quantitative and qualitative analysis, with advanced skills in statistical tools such as Python, SQL and specialized libraries (Pandas, Sci-kit learn). Expert in EDA (Exploratory Data Analysis) and data cleaning processes that ensure high-quality insights.

Experience in data visualization using Plotly, Tableau and Matplotlib, and in technology systems management. Demonstrated ability to design research, process large datasets with big data technologies, and leverage AI-assisted analytics for enhanced productivity. Proven expertise in stakeholder communication, cross-functional collaboration, and translating complex technical findings into actionable business insights for strategic decision making.

Technical Skills

Programming & Analysis

Python (Pandas, Sci-kit learn, NumPy)
SQL & SQLAlchemy
Jupyter Notebook
SPSS, Statmodels
Machine Learning
EDA (Exploratory Data Analysis)

Data Visualization

Plotly & Dash
Tableau
Matplotlib & Seaborn
Interactive Dashboards
KPIs & Metrics

Methodologies

Quantitative & qualitative analysis
Predictive models
A/B Testing
Advanced statistical analysis
Feature Engineering
Data Cleaning & Quality Management

Tools & Systems

Git & GitHub
JIRA, Zendesk
INTERTEL
Database management
Network administration
Big Data Processing
AI-Assisted Analytics

Professional Competencies

Communication & Storytelling

Data storytelling & narrative building
Executive presentations & reporting
Technical documentation & writing
Visual communication of insights
Audience-tailored messaging

Collaboration & Leadership

Cross-functional team collaboration
Stakeholder management & alignment
Project coordination & delivery
Knowledge transfer & mentoring
Consensus building & negotiation

Analytical & Critical Thinking

Complex problem decomposition
Hypothesis-driven analysis
Business acumen & strategic thinking
Data-driven decision framework
Quality assurance & validation

Adaptability & Growth

Continuous learning & upskilling
Technology adaptation & innovation
Change management & flexibility
Time management & prioritization
Resilience & stress management

Work Experience

Data Partner – Business Writer (Freelancer)

TELUS Digital | Remote

11/2025 - Present

Analysis and validation of data-driven content used for large language model training.
Documentation of criteria and findings to ensure consistency, quality, and knowledge transfer.

Data Analyst

Practicum Bootcamp | TripleTen

08/2024 - 03/2025

Developed 5 analytical projects applying advanced data science and machine learning methodologies
Implemented predictive models using logistic regression and random forest to identify customer churn patterns
Designed and executed A/B experiments to evaluate recommendation algorithms, improving data-driven decision making
Developed interactive visualizations with Plotly, Dash and Matplotlib to communicate key findings to stakeholders
Created complex SQL queries for bibliometric analysis, identifying significant correlations between business variables
Developed a performance evaluation system using Python and advanced statistical techniques to optimize operational KPIs
Conducted comprehensive EDA processes and implemented data cleaning protocols, ensuring high-quality datasets for analysis and modeling
Led cross-functional collaboration with stakeholders to translate business requirements into analytical solutions, improving decision-making processes across multiple departments

Voice & Data Technician

National Electoral Institute

01/2024 - 07/2024

Managed installation and configuration of critical communication systems, ensuring operability during electoral processes
Resolved technical incidents in voice and data networks with an average response time of less than 2 hours
Provided specialized technical support to more than 50 users, improving electoral staff productivity
Participated in implementation and maintenance of network infrastructure for 2024 federal elections, ensuring 99.8% connectivity
Collaborated in designing security protocols to protect electoral data integrity

Managed Services Engineer

INTERSEL

10/2021 - 11/2023

Implemented monitoring solutions for technological infrastructure of multiple corporate clients
Designed monthly dashboards using visualization tools to present critical KPIs to management
Analyzed complex technical problems and developed optimized solutions through advanced SQL queries
Documented technical processes and operational procedures, improving knowledge transfer by 40%
Implemented database management improvements that increased operational efficiency by 15%

Technical Support Lead

Soriana Distribution Center

2018 - 2019

Administered critical computer systems for distribution center operations processing over 10,000 products daily
Developed periodic reports using analytical tools to support operational decision making
Implemented preventive maintenance solutions that reduced technical incidents by 25%
Managed operational databases and prepared analytical reports for regional logistics management

Featured Technical Projects

Model Fitness – Customer Retention Predictive Analysis

Developed a predictive model using logistic regression and random forest to identify customers at high risk of churn. Implemented feature engineering techniques with Python and Pandas, improving model accuracy by 15%. Designed a risk scoring system that enabled prioritized retention actions.