Empowering businesses with AI-driven solutions.
Optimizing ATM Management for CaixaBank
As a senior data application developer, I automated data collection and processing entirely using Qlik Sense, a powerful Business Intelligence tool. I designed a centralized dashboard that integrates all relevant data—from ATM statuses to maintenance technician tracking.
The system updates every 15 minutes, providing real-time insights to over 40 team members. Additionally, automated detailed reports are shared with CaixaBank, significantly reducing operational costs for Fujitsu.
- 25% reduction in support costs related to ATM and technician management.
- Improved operational efficiency by eliminating manual and disconnected processes.
- Team growth from one member in 2021 to a three-person team I currently lead.
- Increased client satisfaction: The system is now a critical part of ATM maintenance operations.
This project enhanced my technical expertise while allowing me to develop leadership and team management skills in complex projects.
My ability to align advanced technology with business needs was key to the project’s success.
Automating Call Center Transcription Processing
I developed an advanced Natural Language Processing (NLP) model using a secure internal instance of Microsoft Azure. The solution automatically summarizes, processes, and classifies call transcripts using AI, ensuring data confidentiality within a controlled environment.
With just a few clicks, the system processes thousands of transcripts, eliminating manual intervention and improving analysis accuracy.
- 90% reduction in transcript processing time, allowing the team to focus on strategic tasks.
- Significant optimization of resources, cutting operational costs linked to manual analysis.
- Improved accuracy by removing human errors.
- Full compliance with data security standards through an internal Azure-based solution.
This project deepened my expertise in NLP and AI models for large volumes of unstructured data. I also strengthened my ability to design solutions that balance innovation and security in high-confidentiality environments.
Predicting ATM Failures for Ibercaja
I led a three-person team to develop a predictive Machine Learning model using Microsoft Fabric and XGBoost, one of the most advanced classification algorithms.
The model analyzes internal ATM logs to forecast failures, enabling Ibercaja to take preventative actions before issues arise.
- Accurate failure predictions for 60% of ATMs, reducing downtime and improving customer satisfaction.
- Optimized operational costs by shifting to preventive rather than reactive maintenance.
- Enhanced efficiency in technician allocation, improving response and resolution times.
This project honed my skills in leading innovative teams and implementing advanced predictive models.
It also reinforced my ability to manage projects combining data analysis with operational improvements.
Big Data and Spark Training for IEBS
I developed a practical, dynamic teaching approach, creating hours of video content and hands-on exercises that students could apply directly to real-world use cases, such as predicting pollution peaks using open Smart City data.
I also provided continuous, personalized assessments to ensure each student progressed at their own pace.
- Consistently excellent ratings across all cohorts, with high student satisfaction.
- 100% course completion for students who submitted practical exercises.
- Significant improvement in student knowledge levels, as measured by pre- and post-course tests.
Teaching strengthened my ability to communicate complex topics clearly and effectively while adapting to diverse learning styles, all with a results- oriented approach.
Predicting Thermal Stress in Farms for Regrowth
I developed a predictive analytics model tailored to each farm’s needs. The model, built with advanced Machine Learning techniques, combines local climate data with internal farm data to provide specific recommendations, such as when to adjust animal housing temperatures to prevent thermal stress.
- Significant reduction in animal thermal stress, improving welfare and productivity.
- Optimized farm resource usage by accurately predicting when climate control is needed.
- Increased profitability by preventing productivity losses due to heat- related illnesses.
This project allowed me to create scalable, customizable solutions for industries like agriculture, applying predictive models in high-impact economic and social scenarios.
It also reinforced my ability to integrate client-specific data with advanced analytics.