I am Jordi, a highly skilled data enthusiast with a passion for leveraging technology to solve complex business problems.
I am passionate about programming, cryptocurrencies, data and stock market analysis.
I earned my degree in Business Administration from the Universitat Autònoma de Barcelona and furthered my education with a master’s degree in Financial Management from the renowned Universitat Pompeu Fabra.
To augment my expertise, I completed the Ironhack bootcamp, where I emerged as the winner of the first edition of the IronDatathon an in-class competition akin to Kaggle contests.
During my time at Ironhack, I honed my skills in Python, SQL, Scikit-learn, Pandas, SciPy, Seaborn, Matplotlib, and various other Python libraries.
My experience extends to Kido Dynamics, where I served as a Data Scientist, gaining valuable knowledge in GeoPandas, Airflow, Superset, AWS, and developing cutting-edge algorithms related to geometries. I also developed a population model and conducted innovative geovisualizations with Folium and Mplleaflet.
I took two years off to focus on personal growth and professional development.
During the first year, I embarked on a journey across Europe, exploring diverse cultures, broadening my perspectives and honing my adaptability in new environments.
In the second year, I dedicated myself to enhancing my programming skills and expanding into front-end development. I learned HTML, CSS, JavaScript, React, and Node, which has significantly broadened my technical abilities and understanding of full-stack development.
I am eager to take on new challenges and opportunities, and I am actively seeking a Data Scientist role where I can contribute my skills and expertise to a dynamic team. I am open to positions both domestically and internationally.
I am confident that my broad experience and skills make me a valuable addition to any team.
Please do not hesitate to contact me for additional information.

Publications

Radius of Gyration as predictor of COVID-19 deaths trend with three-weeks offset

Kido Dynamics

2021

- Lockdowns, both total and perimetral, were the most effective nonpharmaceutical interventions against COVID-19 but also had significant socioeconomic impacts. Decision-makers struggled with predicting the appropriate level of restrictions due to the lack of immediate data on their effects.
- The radius of gyration, derived from mobile phone data of over 13 million users in Spain, aggregates key aspects of human mobility into a sensitive metric that predicts COVID-19 death trends with a three-week offset.
- Analysis showed that when the radius of gyration exceeds 70% of its pre-pandemic level, COVID-19 deaths increase three weeks later, and conversely, deaths decrease when the radius is below this threshold, suggesting it as a reliable predictor and indicating that partial mobility restrictions can be as effective as total lockdowns.
Mobility reduction in Spain after the adoption of covid confinement measures

Institute for Cross-Disciplinary Physics and Complex Systems (IFISC)

2020

- This page reports analyses on how mobility in Spain changed in response to policies aimed at combating the COVID-19 pandemic.
- Using aggregated and anonymized data from mobile phone records provided by Kido Dynamics we chart movement trends after the major mobility and social restrictions imposed by the Spanish government at different geographical scales.
- This work falls under the research carried out in the Distancia-COVID project of CSIC funded by AENA

Experience

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Senior Data Scientist

Caixabank
2024 - Actual

- Driving modernization efforts by leading the migration of an internal Python framework to Google Cloud Platform (GCP), ensuring scalability, improved performance, and alignment with cloud-native best practices.
- Maintaining and optimizing the internal Python library, implementing updates, bug fixes, and enhancements to support seamless functionality across teams.
- Implemented automated model registration with MLflow, streamlining the process of tracking, versioning, and deploying machine learning models for production use.
- Collaborating across teams to identify improvements for the internal library, ensuring compatibility with evolving tools, technologies, and business requirements.
•
Data Scientist / Backend Developer

Kido Dynamics
2019 - 2022

- Developed a population model using Scikit-learn to analyze demographic trends and patterns. Also used BeatifulSoup and Selenium to retrieve the data.
- Created several endpoints using FastApi.
- Designed and implemented visually appealing geo-visualizations using Plotly and Geopandas to enhance data exploration.
- Developed algorithms to merge polygons based on specific criteria, enhancing spatial data analysis.
- Created automation pipelines utilizing Python scripts and Airflow to streamline data processing and analysis.
- Constructed interactive dashboards using Apache Superset to facilitate data-driven decision-making.
- Proficient in managing large data files exceeding 100GB in size using Python.
•
Senior Auditor

KPMG
2016 - 2019

- Analysis of the business process, design evaluation and quality of internal controls.
- Analysis of the credit risk areas under local regulations (Bank of Spain) and IFRS.
- Analysis of the financial and solvency situation of the main clients of the banking entities.
- Identify opportunities for performance improvement.
- Directly responsible for reporting to Managers and Partners.
- Responsible for the management and coordination of teams of 2 to 5 people.
- Client portfolio: Deutsche Bank, SAE and subsidiaries, Banca March, Institut Català de Finances (ICF), Caixa d'Arquitectes, Private Bank Degroof, Caixa d'Enginyers.