Buenos Aires
I left Buenos Aires in the aftermath of Argentina’s economic crisis. That abrupt change forced me to read the environment, adapt and start again.
HERNÁN FALBO ÁLVAREZ
I work at the intersection of data, business, artificial intelligence and product: understanding complex problems, giving them structure and turning them into tools that help people make decisions, investigate, or work better.
I am not interested in adding technology for its own sake. I care about information having context, decisions being traceable, and what is built fitting the reality of the people who use it.
02 · BUENOS AIRES → MADRID
I arrived in Spain in 2002, after Argentina’s economic crisis. I started by working and adapting to a new context; specializing in data would come later, driven by a need that was far more personal than professional.
I left Buenos Aires in the aftermath of Argentina’s economic crisis. That abrupt change forced me to read the environment, adapt and start again.
I arrived in 2002 and started working. Over time, a personal need would turn learning and understanding into something much more concrete, and data would begin to take on a different role in my journey.
03 · WAY OF WORKING
Before choosing a technology, I try to understand what is happening, what information exists, who needs to use it, and what decision the system should make easier.
What problem needs solving and for whom.
What information matters and how it is organized.
Which pieces were disconnected.
What really needs to work.
How it is interpreted, maintained and questioned.
A system that nobody can interpret, maintain or question is not finished yet.
04 · LAYERS THAT ACCUMULATED OVER TIME
My career did not start in data. It started with working, understanding business and learning to operate in different contexts. Going deeper into data came later, when organizing complex information stopped being only a useful skill and also became a personal need for understanding.
Constraints, priorities and the why behind a decision.
Modelling, visualization and a shared view of business evolution.
New ways to analyze relationships, signals and automation.
Queryable knowledge, context, limits and governance.
Connecting all the layers around a real user need.
ACROSS ALL AREAS05 · PROFESSIONAL EXPERIENCE
Experience serves here as credential and context, not as a second timeline. The organizations show where the work was applied; they do not repeat the conceptual evolution above.
An environment where analysis, business, information models and BI have to translate into understandable, usable decisions.
A stage that consolidated the connection between operational needs, forecasting, analysis and information solutions without separating the business problem from its implementation.
This is where I consolidated pricing, margins, profitability, KPIs and reporting, together with a principle I still use today: understand the business first, then use data to explain, measure and improve it.
A one-off collaboration that brought analysis into a different context and reinforced the value of working with clear, traceable and useful information.
06 · EDUCATION
Specializing in data did not start with a degree. Formal education came later to bring method, tools and technical language to a search that had already begun.
07 · WHEN DATA STOPPED BEING ONLY WORK
When my son was born, I found myself facing a complexity that, as a father, I needed to try to understand. I wanted to understand better what was happening, why, and what he might need; not to take the place of a doctor, but to be able to ask better questions, organize the information and support him with better-informed judgment. That need was what pushed me to go much deeper into data, and it ultimately changed my professional path as well.
Discover EchoFather →08 · WHAT I BUILD TODAY
Three territories summarize where I focus my work today. They combine differently depending on the problem, the context and the decision the system needs to support.
Models, KPIs, visualization and information systems for understanding what is happening and supporting decisions.
BI · business evolution · analysisComplex document-based information, semantic search, evidence retrieval, privacy and traceable knowledge systems.
Document AI · research · knowledgeReal workflows, information architecture, functional prototypes and tools designed around how people work.
HealthTech · UX · product09 · PRINCIPLES
These are not slogans detached from the projects. They are criteria that should be recognizable in how the work is built.
It is organized.
10 · CLOSING
Understand the problem. Give structure to the information. Connect what was separate. Build something useful. And be able to explain it.