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The Journey

From Gamer to ML Architect

I learned to love systems by optimizing game strategies. Today, I use that same obsession to build production ML engines that move millions of dollars.

Games lit the spark
The Origin

Games lit the spark

Hours spent on strategy games taught me systems thinking, probability, and how small tweaks compound. I started keeping little scripts and spreadsheets to track performance—my first taste of experimentation.

  • Optimization mindset
  • Iterating fast on results
First startup shipped
College Years

First startup shipped

With a few friends, I launched simple tools helping local businesses plan deliveries. We bootstrapped the stack, handled user feedback, and shipped weekly updates.

  • Zero to One building
  • Prioritization under constraints
Barcelona Supercomputing Center
First Research

Barcelona Supercomputing Center

Built a fire evacuation routing system that won 1st place at a national AI congress. This was my gateway into optimization—seeing algorithms impact real-world safety.

  • Simulation & Optimization
  • Academic rigor -> Real world
Data Analyst Foundation
Industry Entry

Data Analyst Foundation

At Baxter, I blended sensor data and operations metrics into dashboards. It grounded me in data quality, stakeholder communication, and measurable outputs.

  • Data reliability at scale
  • Visual storytelling
Formalizing the Math
Master's Degree

Formalizing the Math

Graduate work on vehicle routing (VRPTW) gave me the tools to connect algorithms with business constraints—exactly what I now apply in production systems.

  • Advanced Logistics
  • Applied CS Theory
From Insights to Impact
Data Scientist

From Insights to Impact

Driven growth via market mix models and churn prediction. Focused on defining metrics, building models, and evangelizing adoption with PMs.

  • Model Validation
  • Cross-functional adoption
Senior DS & AI/ML Engineer
Current Role

Senior DS & AI/ML Engineer

Now I architect end-to-end systems: multi-agent GenAI platforms at CVS Health, recommenders at Walmart, optimization at DHL. The goal stays the same—turn models into measurable business value.

  • MLOps & Observability
  • Production-grade pipelines

The story is nice.
The results are better.

See how 8+ years of obsession with optimization translates into production systems that move KPIs at CVS Health, Walmart, DHL, and Huawei.