About Me
My journey as a data scientist is driven by the power of transforming raw data into insights that create tangible value and shape better decisions.
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My Professional Journey
I'm a data scientist specializing in building advanced analytics systems that solve complex business problems through the strategic application of machine learning and artificial intelligence. My expertise centers on creating customized solutions that transform data into actionable intelligence, providing organizations with the insights they need to make better decisions.
With experience spanning multiple industries including retail, real estate, financial services, and electoral analysis, I've developed a versatile skillset that allows me to quickly understand domain-specific challenges and develop tailored data science approaches. My academic background in Data Science from UC Berkeley provides a strong foundation in statistical methods and machine learning techniques.
Currently pursuing a Master's in Applied Artificial Intelligence at Tecnologico de Monterrey, I'm deepening my expertise in cutting-edge AI methodologies while maintaining an active professional practice, creating a powerful synergy between theoretical knowledge and practical application.
My approach combines technical excellence with business acumen—I don't just build models, I deliver solutions that create measurable value. Whether it's optimizing inventory systems, enhancing customer experiences through personalization, or providing location intelligence for strategic decisions, I focus on translating complex algorithms into business impact.
Career Timeline
Started Masters in Applied Artificial Intelligence
Started Masters in Applied Artificial Intelligence
Enrolled in Tecnologico de Monterrey's prestigious MNA program to deepen expertise in cutting-edge AI methodologies and applications.
Joined PRODENSA as Python Developer
Joined PRODENSA as Python Developer
Contracted to develop AI tools for industrial document processing and knowledge management, implementing custom NLP solutions and intelligent data extraction systems.
Joined STRTGY
Joined STRTGY
Became the lead data scientist at STRTGY, developing advanced geospatial analytics solutions for strategic decision-making.
Graduated from UC Berkeley
Graduated from UC Berkeley
Completed Bachelor's degree in Data Science with honors, focusing on machine learning and statistical analysis.
Data Scientist at BlackPrint Technologies
Data Scientist at BlackPrint Technologies
Built property data analytics solutions and implemented geospatial intelligence for real estate market analysis.
Data Analyst at AGM Analytics
Data Analyst at AGM Analytics
Performed user engagement analysis for SaaS platforms, analyzing metrics like DAU, MAU, and feature adoption rates to improve user retention and product development.
Professional Values
Data-Driven Excellence
Committed to delivering solutions backed by rigorous analysis and empirical evidence, ensuring decisions are based on facts rather than assumptions.
Continuous Learning
Dedicated to staying at the forefront of data science and AI advancements through consistent self-education and formal learning opportunities.
Ethical AI Advocate
Champion responsible AI development that prioritizes fairness, transparency, and human-centered design in all technical implementations.
Business-Technology Bridge
Skilled at translating complex technical concepts into business value and communicating effectively across technical and non-technical teams.
Areas of Professional Interest
Geospatial Machine Learning
- › Location intelligence algorithms
- › Geographic pattern recognition
- › Spatial prediction models
Multimodal AI Systems
- › Vision-language models
- › Cross-modal information retrieval
- › Multimodal embeddings
Responsible AI
- › Fairness in machine learning
- › Explainable AI methods
- › Ethics in data science
Business Intelligence
- › Strategic decision support systems
- › Predictive analytics
- › Interactive data visualization
My Professional Approach
Discovery
Thorough understanding of business context, stakeholder needs, and existing data landscape through collaborative exploration.
- • Stakeholder interviews
- • Data inventory
- • Problem framing
- • Opportunity identification
Solution Design
Systematic approach to architecture and algorithm selection based on problem requirements, data constraints, and business objectives.
- • Architecture planning
- • Method selection
- • Prototype design
- • Feasibility validation
Implementation
Iterative development with continuous testing and refinement to ensure solutions meet both technical and business requirements.
- • Data pipeline construction
- • Model development
- • Validation testing
- • Performance optimization
Integration
Seamless deployment and knowledge transfer ensuring solutions create sustainable business value with measurable impact.
- • Documentation
- • Stakeholder training
- • Systems integration
- • Impact measurement
Interested in Working Together?
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision. Let's connect and explore how we can create data-driven solutions together.