About me

Mathematician specialised in data science and geospatial analysis. I combine a rigorous statistical background with hands-on experience in data modelling, data engineering and visualisation.

At Nielsen I implemented Bayesian statistical models and time series for leading CPG sector clients in the United States, translating complex results into actionable marketing KPIs. Currently at Grupo Noa's I design and automate data pipelines, ETL/ELT processes and REST API integrations, building Power BI dashboards to support data-driven decision making.

My training as an Erasmus Mundus scholar in Geospatial Technologies (Universitat Jaume I · University of Münster) allows me to incorporate advanced spatial analysis as an additional layer: geospatial predictive modelling, machine learning applied to location data, raster analysis and analytical cartography.

Some insights

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    Mathematics & Statistics

    I have a strong background in pure and applied Mathematics. After almost a decade of rigorous studying Mathematics, I have developed a good level of abstraction and a creative mind when dealing with any problem. I have conducted research as part of financed research programs in my home country (Mexico) and abroad (Spain). Moreover I have experience in scientific environments, as I have presented oral and written works in my research path. In my bachelor's thesis project , I studied Differential Topology and in my personal projects and work experience I mastered applied topics, including Probability and Statistics.

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    Machine Learning

    I possess a strong understanding and +3 years experience on Machine Learning theory and methods. In my work experience at Nielsen I conducted data modelling tasks using regression methods. A key ingredient implied a deep understanding of the models used and the main methods to tailor data accordingly and present insightful results. Furthermore, I formally conducted a core study of Deep Learning and other state-of-the-art algorithms as part of my postgraduate studies.

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    Programming

    In the past +5 years, I have been able to develop my programming skills in different contexts. As a student of the BSc. Physics during two years, I was first exposed to Linux environment and to data analysis and processing with Python as part of daily tasks in the lab. Lately, as part of my postgraduate studies, I have acquried a strong knowledge of ETL and modelling methods using Python, SQL, and R. Furthermore, I possess experience in Web Technologies using JavaScript, HTML, and CSS.

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    Geospatial advocate

    Since I was a teenager, I have been deeply engaged in understanding our natural and social environments. I was able to represent my country in the International Geography Olympiad twice (Cracow, Poland 2014 and Tver, Russia 2015). Recently, I developed my technical skills in Geographic Information Systems (GIS) in integration with Web Technologies and Machine Learning, as part of my postgraduate studies. I am passionate about technology and its power to study and solve spatial problems.

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    Languages enthusiast

    I have always loved to learn languages. My keen interest in them has opened me the opportunity to make research stays and studies in several countries (Spain, UK, Germany). I consider myself a strong defensor of linguistic and cultural diversity.

My skills

Data Science & ML
Python R SQL Scikit-learn Keras TensorFlow Time Series Bayesian Stats
Data Engineering
ETL/ELT REST APIs Power BI Power Query Power Automate Git Pandas
Geospatial
QGIS ArcGIS PostGIS GeoPandas Leaflet.js Raster analysis
Web
JavaScript HTML CSS jQuery

Resume

Read CV

Experience

  1. Data Analyst & BI Developer

    ● Current
    Grupo Noa's, Castelló de la Plana, Spain (04/2025 – Present)

    > Design, optimization and automation of data pipelines (Python, SQL, Power Automate), improving data processing efficiency.

    > Development of ETL/ELT processes integrating REST APIs, CRMs and databases.

    > Exploratory data analysis and data modelling to support data-driven decision making.

    > Definition and calculation of business KPIs and metrics (SQL, Python and Power Query).

    > Creation of interactive dashboards and visualization solutions (Power BI).

    > Automation of workflows with Power Automate, reducing manual tasks.

    > Collaboration with stakeholders and technical support for continuous improvement of data-driven processes.

  2. Grant holder

    Erasmus Mundus Master in Geospatial Technologies (09/2023 — 03/2025)

    > Developed Machine Learning models to forecast the consumption of electricity in the military facilities of the UN in Sudan (SQL, R, Git) and flood classification model with Deep Learning (QGIS, R, Keras, TensorFlow). > Specialisations: Data Science, Machine Learning, Statistics (Python, R), Databases (SQL), Web Programming (JavaScript, HTML, CSS), and GIS (ArcGIS, QGIS, PostGIS).

  3. Modelling Analyst

    Nielsen (10/2022 - 08/2023)

    > Implemented machine learning modelling to drive insights from media and sales time series for US and EU clients leading the CPG sector through attribution models (Unilever, Johnson&Johnson, Ferrero).

    > Translated model results to benchmark marketing KPIs presented to the client (Power Query, Excel), to measure the impact of their marketing strategies.

    > Collaborated with international teams (data processing, modelling, and customer success teams) across multiple projects.

  4. Undergraduate researcher

    Universidad de Sevilla (09/2021– 12/2021)

    > Conducted undergraduate thesis research at the Department of Geometry and Topology.

    > Presented results at a weekly seminar held at the university.

  5. Assistant professor

    Universidad Nacional Autónoma de México (08/2019– 07/2021)

    > Taught Differential & Integral Calculus I-III at the bachelor's degrees in Mathematics, Physics, and Actuarial Sciences.

    > Prepared and presented class material. Graded exams and assignments.

Education

  1. MSc. Geospatial Technologies

    Universitat Jaume I, Spain Universität Münster, Germany Universidade NOVA de Lisboa, Portugal 09/2023 - 03/2025

    > Grade: 9.22/10.00.

    > Specialisations: Data Science, Machine Learning, Geostatistics, Databases, Web Programming, and Geospatial Analysis.

    > Thesis: Energy consumption modelling in IoT-surveyed peacekeeping missions

  2. Visiting Student

    University of Bristol, UK 01/2020 - 07/2020

    > Grade: First.

    > Specialisations: Partial Differential Equations, Logic, Number Theory.

    > Membership of the Bristol Data Science Society.

  3. BSc. Mathematics

    Universidad Nacional Autónoma de México, Mexico 08/2016 – 10/2022

    > Grade: 10.00/10.00.

    > Specialisations: Mathematical Analysis, Probability, Statistics, Programming, Vectorial Mechanics, Partial and Ordinary Differential Equations, Topology.

    > Thesis: Morse Homology and its Applications

Portfolio

  • IoT prediction plot

    Modelling of IoT-surveyed UN camps

    Forecast and time series

    I developed this project as part of a UN collaboration between Universitat Jaume I and the United Nations Global Service Centre, building time series forecasting models for energy consumption prediction in UNISFA facilities in Abyei. The workflow integrated SQL and R for modelling and analytics, plus Git for version control and reproducible delivery. Achieved strong predictive accuracy enabling reliable energy consumption forecasting for facility planning.

  • Madrid pollution map

    Madrid pollution quarter-level trend assessment in 2023

    Data Analysis and GIS

    I assessed neighbourhood-level pollution patterns in Madrid using GIS-driven spatial interpolation, vectorial datacube aggregation and time series analysis from sensor-level observations.

  • Traffic volume classification

    Traffic volume classification

    Supervised learning

    I built a supervised learning workflow for traffic volume classification, benchmarking Random Forest, AdaBoost, XGBoost, Deep Learning and kNN models.

  • Flood segmentation maps

    Flood modelling with Convolutional Neural Networks

    Deep Learning

    I built an end-to-end deep learning pipeline for flood detection using image segmentation on multispectral satellite imagery, with QGIS-based preprocessing and raster analysis. The modelling stage combined CNN architectures in Keras and TensorFlow to classify flooded areas during the 2024 Brazil events.

  • Video game iterface image

    Bejeweled Web Videogame

    Web development

    In this project, a Bejeweled-like web videogame inspired by the Splendor board game was developed. The handler's code is written in pure JavaScript and the styling follows a "from scratch" format in CSS to showcase full understanding of these languages.

  • Air pollution image

    Castelló pollution prediction

    Machine Learning

    I developed a machine learning workflow in R for pollution forecasting, including sensor-wise time series preprocessing and LSTM modelling to predict pollution dynamics in Castelló during 2023.

  • Inequality map

    Gender Data Analysis

    Data Analysis and GIS

    Study on gender financial inequality in Mexico and Brazil. We explored oficial dataset on income by gender and state in both countries. Through data transformations and visualizations, it is possible to see the spatial distribution of income by gender, the relative (women/men) income, and the participation in labor by gender.

  • App interface with list of campings

    Campings of Castelló

    Web development

    Development of a app using jQuery mobile to retrieve the location of the user and provide a list with nearby camping sites in the province of Castellon.