Spectral Data Modeling Platform
Web application for functional spectral data analysis, enabling researchers to explore, model and visualize complex spectra with reproducible pipelines.
Next.jsFastAPIPythonPlotlyPostgreSQL
Data Science & AI Engineer
Lucas García García
Data Science & Artificial Intelligence Engineer based in Madrid, Spain. I design and build production-ready machine learning systems, turning data into reliable tools for researchers, clinicians and industry teams.
I'm especially interested in applied AI, robust ML pipelines and data products that deliver measurable impact beyond academic prototypes.
Location
Madrid, Spain
Current focus
Applied ML, production-grade data systems
Open to
Data / ML engineering & applied AI roles
About
I recently graduated in Data Science and Engineering from Carlos III University of Madrid, including an Erasmus year at KU Leuven in Belgium where I focused on master-level courses in AI and data analysis. During my studies I gravitated towards projects that required turning messy, real-world data into reliable tools.
I have built production-oriented AI systems including a web platform for functional spectral data modeling used in a university research lab, and a medical ultrasound prediction system developed in collaboration with Hospital Gregorio Marañón. These experiences taught me how to bridge research ideas with robust engineering.
At Renault's Digital Transformation department I worked on internal KPI analytics, logistics optimization and predictive modeling, with solutions deployed and used by non-technical teams. I enjoy collaborating with stakeholders, understanding constraints and shipping systems that are maintainable, monitored and actually used in production. I'm particularly interested in applied AI, machine learning systems, data engineering and industry-focused innovation.
Projects
Renal Ultrasound Classification System
End-to-end pipeline for predicting relevant clinical outcomes from ultrasound data in collaboration with Hospital Gregorio Marañón.
PythonPyTorchMLflowJupyterDocker
Renault KPI Analytics Dashboard
Internal KPI analytics web application for the Digital Transformation department at Renault España Comercial.
TypeScriptReactFastAPISQLDocker
Experience
Oct 2024 – Jun 2025
Renault España Comercial S.A.
Engineering Intern – Digital Transformation
- Designed and deployed an internal KPI analytics web application.
- Developed predictive forecasting models to support operational planning.
- Worked on logistics optimization initiatives with measurable efficiency gains.
- Collaborated closely with cross-functional and non-technical teams.
2023 – 2024
Erasmus at KU Leuven
Focus on AI & Data Analysis master-level courses, strengthening foundations in machine learning, statistical modeling and advanced analytics.
Education
BSc in Data Science and Engineering
Carlos III University of Madrid · 2020–2025
- Final Year Project: web application for functional spectral data analysis and modeling.
- Medical AI project in collaboration with Hospital Gregorio Marañón focused on ultrasound prediction.
Strong foundations in mathematics, statistics, machine learning and software engineering, complemented by hands-on projects and close collaboration with researchers and industry partners.
Skills
Programming
- Python
- TypeScript / JavaScript
- SQL
Frameworks
- Next.js & React
- FastAPI
- Jupyter
- TailwindCSS
AI / Data
- Machine Learning & Predictive Modeling
- Statistical & Bayesian Modeling
- Neural Networks
Tools
- Git
- Docker
- Voilà
- Plotly
Contact
I'm open to roles and collaborations where I can help design, build and deploy data-intensive systems and machine learning solutions with real business or research impact.
© 2026 Lucas García García