Markel Ramiro
Data Scientist & ML Engineer
Building intelligent data solutions that deliver real business impact
About Me
I'm a Data Scientist and Machine Learning Engineer passionate about transforming data into actionable insights. With expertise in AI/ML model development and deployment, I help organizations leverage data-driven decision making for competitive advantage.
AI & ML Expertise
Developed and deployed AI solutions including anomaly detection systems, predictive models, and natural language processing applications.
Data Pipeline Engineer
Experience building robust data pipelines and ETL processes that ensure data quality and availability for analytics workloads.
Cloud-Native Deployment
Skilled in containerizing ML applications and deploying them to production environments using Docker and Kubernetes.
Professional Profile
As a Data Scientist and ML Engineer with a degree in Artificial Intelligence, I specialize in developing data-driven solutions that solve real business problems. My expertise includes machine learning, data engineering, and deploying AI systems in production environments.
Currently working at Devol as a Data & AI Engineer, I'm leading the development of LLM-based document extraction systems and natural language interfaces. I'm passionate about using cutting-edge technologies to create practical applications that deliver measurable business value.
I have a strong foundation in Python, ML frameworks, and cloud technologies, with experience in the entire ML lifecycle from data preparation to model deployment and monitoring.
Education
My formal education and professional development journey
BSc in Artificial Intelligence
University of the Basque Country (UPV/EHU)
Member of the 1st graduating class of the AI program. Final Project: 'Anomaly detection and deployment in Kubernetes' (Grade: 9/10).
Highlights:
- •Relevant courses: Machine Learning & Neural Networks, Massive Data Processing, Temporal Data Analysis
- •University Entrance Exam Score: 12.24/14 (87.4%)
Applied Data Science Program
Zrive
Intensive 15-week program focusing on applied data science with real business problems, production-ready skills, and industry mentorship.
Highlights:
- •7 comprehensive modules: API integration, EDA, statistical learning, advanced ML, and system design
- •Real-world projects with messy datasets and business constraints
- •Production-ready development practices with proper testing, versioning, and deployment
- •Industry mentorship from professionals at Meta, Vodafone, and Revolut
Technical Skills
My toolkit for solving complex data challenges
AI & Machine Learning
OpenAI
Python
TensorFlow
PyTorch
Scikit-learn
Hugging Face
LangChain
Pandas
NumPyBackend & Infrastructure
Kubernetes
Docker
AWS
Azure
Flask
Node.js
Prometheus
GrafanaTechnology Stack
Zrive Applied Data Science Program
Intensive 15-week program developing industry-ready data science skills through hands-on projects, real-world case studies, and collaboration with industry experts from leading tech companies.
Program Highlights
- 🎯50+ hours of live online sessions with industry experts
- 👥Individual mentoring with professionals from Vodafone, Revolut, and Meta
- 🏢Real industry project with business partner collaboration
- 🛠️Production-ready skills with industry tools and best practices
Learning Journey
🎯 Core Philosophy
Unlike traditional academic programs, Zrive focuses on applied data science with real business problems, messy datasets, and production constraints. Every module builds practical skills that translate directly to industry work, emphasizing business impact over theoretical perfection.
Direct certificate link: markelramiro.com/certificate
Featured Projects
A selection of data science and machine learning projects showcasing my technical abilities
Sumauto Churn Prediction
Collaborative churn prediction project for Sumauto (vehicle classified ads platform) developed with Komorebi consultancy. Building ML models to predict advertiser abandonment based on performance and behavioral metrics.
Anomaly Detection System
Developed an anomaly detection system for API performance monitoring using statistical methods and machine learning. The system processes ti...
Financial Prediction Model Diagnosis
Model diagnostics for S&P 500 outperformance prediction. Identified data leakage, implemented SHAP analysis and PCA feature engineering to s...
Wippass - Event Ticketing Platform
Full-stack ticketing platform that processed €25,000+ in transactions for local events.
DocMind LLM Document Extraction
Led development of an LLM-based system that automatically extracts structured data from unstructured documents, reducing manual processing t...
Professional Experience
My journey in the world of data science and machine learning
Data & AI Engineer at Devol
Leading AI development initiatives for enterprise clients, focusing on document processing automation, natural language interfaces, and predictive analytics. Responsible for end-to-end model development, from data preparation to production deployment.
AI Integration Specialist at Nomada Omnimotion
Contributed to VR technology innovation by developing AI-powered pose estimation systems for omnidirectional treadmills. Engineered sensor fusion algorithms for real-time motion data integration.
Founder @ Wippass
Built and deployed a complete ticketing platform handling €30,000+ in transactions for local events. Achieved multiple sold-out events (900+ attendees) and was featured in El Referente magazine for entrepreneurial innovation.
B.Sc. in Artificial Intelligence @ University of the Basque Country
Focus on machine learning, neural networks, and data processing. Final project on anomaly detection with Kubernetes deployment (Grade: 9/10).
Contact Me
Interested in working together? Reach out through any of these channels.