// Data-Driven Profile

Analytical Profile
Luis Angel Sánchez Aguilar

Statistical insights extracted from 5+ years of professional trajectory — scale, impact, sectors, and research. Everything a recruiter needs to see at a glance.

S/12M+
Business Impact
Projected annual savings, documented
145M+
Records Processed
Across all production ML projects
5
Papers Published
IEEE + Journals + 1 in review
3
Sectors Served
Finance, Industry, Agriculture
100%
Production Rate
All ML projects deployed to prod
Business Impact
Impact by Project
Quantified business value delivered — savings, conversions, new revenue units
Data Engineering
Data Scale per Project
Records processed in production (log scale) — demonstrates enterprise-grade ML experience
Sector Distribution
Industry Exposure
Time & projects by sector
Technical Depth
Skill Radar
Proficiency across key domains
Research Output
Publications by Year
Research + industry balance
Career Timeline
Professional Trajectory — Role Seniority & Specialization Over Time
From Mechatronics Engineer (2021) through ML Engineer to Senior Data Scientist Consultant (2026) + Physics & Quantum Computing in parallel
Technology Stack
Tools & Frameworks Used in Production
Frequency of use across all professional projects
Model Performance
ML Approaches vs. Complexity
Project complexity (x) vs. team size (bubble size) vs. data scale (y)
// Insights

Pattern Recognition — What the Data Reveals

📈
Exponential Data Scale Growth
Progressed from 10M records in early projects to 100M+ records in the most recent deployment — demonstrating systematic experience with enterprise-scale data infrastructure.
🎯
Research → Production Bridge
Unique combination of 5 published papers and 6 production ML systems — rare in industry. Can design, validate, and ship models grounded in academic rigor.
💰
Documented ROI
S/12M+ projected savings documented in a single project. Additional impact includes a new business unit created from unsupervised ML insights and +5% credit conversion uplift.
🧠
Multidisciplinary Foundation
Mechatronics → ML → Data Science → Physics + Quantum Computing. The breadth enables cross-domain pattern recognition not found in pure CS/Statistics profiles.
🏭
Sector Versatility
Delivered production ML in Finance (credit risk, propensity), Industry (demand forecasting), and Agriculture (crop optimization) — domain knowledge transfers across industries.
⚗
End-to-End Ownership
Every project listed went to production. Covers full stack: statistical design, model selection, cloud deployment (GCP/Azure), APIs, retraining pipelines, and stakeholder reporting.
All data sourced from professional experience and published research · © 2026 Luis Angel Sánchez Aguilar
View Full Portfolio