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Joaquín Asensio

Joaquín Asensio

Business/Data Analyst

Tecnología / Internet

Buenos Aires, Buenos Aires C.F.
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Sobre Joaquín Asensio:

Over 3 year of working experience in consulting, technological and administrative areas. I´m a self-motivated and progress-driven professional in the constant search for self-improvement. In the last years I have strengthen my abilities in reporting, business and data analysis, and I´m 100% sure that with my backgroung in business management and data science I will be a great addition to any company.

Experiencia

Over 3 years of work experience as a Business Analyst at Economic Trends in Argentina. During this time I´ve got the oportunity to work with well-known companies in the masive consumer good industry as well as important commercial chambers. Some of the proyects worth mentioning:

- Customer satisfaction analysis for well-known consumer goods 
company. Succeeded in increasing customer satisfaction by 15%, by designing and tracking KPI’s and developing alerts reports.

- Enhance of costs systems of commercial chambers, such as: CIMCC, ACLISA, FAEC, among others. This decreased response time by 80% and cut human error by 95%.

- Successfully developed an application capable of maintaining data from singular companies of the technological industry anonymous.

- Internal implementation of agile methodologies that improved team work and reduced bottleneck situations.

Educación

Universidad Empresarial Siglo 21, Córdoba Capital

2017-02 to 2021-05

Bachelor in Business Administration, Business

Digital House - 160 hours course

2021-01 to 2021-11

Data Scientist; Where I got solid knowledge of machine learning models and the use of different Python libraries for the extraction, processing and analysis of large amounts of data.

  • Designed an algorithm that analyze and cleans real estate information and predicts properties values according to location, surface, amenities among others.
  • Designed a recommender system that takes user input and returns the best possible recommendation according to personal preferences and users’ similarities. 

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