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 part-time program designed to develop technical and practical skills in Data Science.
Currently at: Module 3: Fundamentals of Statistical Learning
Highlights:
- •Exploratory Data Analysis projects with real-world datasets
- •Statistical Learning and ML fundamentals including linear models, regularization techniques, and evaluation metrics
- •Currently working on ML classification problems for e-commerce applications
- •Upcoming: Real business project with industry partner
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
GrafanaDatabases & Frontend
PostgreSQL
MySQL
MongoDB
React
Next.js
Tailwind
SvelteKitTechnology Stack
Zrive Data Science Program
Currently enrolled in an intensive Applied Data Science program, developing industry-ready skills through hands-on projects and real-world applications.
Zrive Applied Data Science
Apr 2025 - Jul 2025
Zrive Applied Data Science is a 15-week intensive part-time program designed for high-performing students and professionals who want to launch their careers as Data Scientists.
The program combines theoretical knowledge with practical application through hands-on projects and real-world case studies, culminating in a 5-week real business project with an industry partner.
Program Highlights:
- •50+ hours of live online sessions with industry experts
- •Individual mock interviews with mentors from companies like Vodafone and Revolut
- •5-week real-world project with industry partner
- •Hands-on experience with industry tools and best practices
Featured Projects
A selection of data science and machine learning projects showcasing my technical abilities
Anomaly Detection System
Developed an anomaly detection system for API performance monitoring using statistical methods and machine learning. The system processes time-series data in real-time and sends alerts when unusual patterns are detected.
DocMind LLM Document Extraction
Led development of an LLM-based system that automatically extracts structured data from unstructured documents, reducing manual processing t...
Time Series Forecasting
Natural Language to SQL
Built a RAG-based system that converts natural language questions into SQL queries, allowing non-technical users to query databases using co...
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.