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The goal of this project was to carry out a retail shop clustering of the enterprise MasM\u00f3vil using the tracking of several quality parameters. In addition to this, we sought to enrich the data of each shop with external datasets.<\/p>\n
As a result, a new data resource was formed with information from the environment of each shop such as the municipal population or the number of nearby competitors. From this new dataset, a model based on a novel dual unsupervised learning paradigm was developed.<\/p>\n
This innovative paradigm is based on clustering static information on the one hand and dynamic information on the other, thus providing a profile of the average behavior of the branch and static features as well as its trend over time. The final result is an outstanding tool capable of supporting the company’s decision making in an effective and clear way, facilitating considerably the management and monitoring of its retail shops.<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.18.0″ _module_preset=”default” custom_margin=”20px||||false|false” custom_padding=”0px||||false|false” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_image src=”https:\/\/storage.googleapis.com\/wp-uploads.bucket.wp.uc3m.es\/wp-content\/uploads\/sites\/70\/2022\/10\/21100252\/aitor.png” title_text=”aitor” _builder_version=”4.18.0″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” theme_builder_area=”post_content” sticky_enabled=”0″][\/et_pb_image][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.18.0″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” theme_builder_area=”post_content” sticky_enabled=”0″]<\/p>\n
FINAL DEGREE PROJECT OF:<\/strong><\/span><\/p>\n AITOR IZUZQUIZA GIMENO<\/strong><\/span><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.18.0″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” theme_builder_area=”post_content” sticky_enabled=”0″]<\/p>\n Degree<\/strong><\/p>\n Carlos III University of Madrid, Sep. 2018 – Jun. 2022 Universidad Nacional de Educaci\u00f3n a Distancia, Sep. 2020 – Jun. 2024 M\u00e1sM\u00f3vil – Back End Developer Sep. 2022 – Actual M\u00e1sM\u00f3vil – Machine Learning Researcher Sep. 2021- May. 2022
Degree in Computer Science and Engineering
Honors in 15 courses, final grade: 8.9\/10.<\/p>\n
Bachelor’s Degree in Mathematics
Honors in 4 courses<\/p>\n
Work Experience
<\/strong><\/p>\n
Responsible for analyzing the technological and methodological needs of the group’s multiple departments, while designing efficient and effective solutions to the problems identified.<\/p>\n
Selected by the Machine Learning research group at Universidad Carlos III de Madrid to work on a project based on data provided by MasMovil Telecomunications.<\/p>\n