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Data scientist
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cabify
Data Scientist
June 26, 2026 – Present
jgonzalezferrer.github.io
November 1, 2021 – November 1, 2021
jgonzalezferrer.github.io — GitHub repository
View Projectacb-database-scraping
May 28, 2017 – June 30, 2017
Code for 'Results and stats of the ACB Spanish Basketball League from 1994 to 2016'.
View Projectspiral-neural-network
February 12, 2017 – February 12, 2017
My first attempt to model neural networks in Tensorflow
View Projecthbase-data-analysis
December 26, 2016 – February 4, 2017
Storing tweets into HBase providing a set of queries for data analysis.
View Projectdiamonds-statistical-regression
December 26, 2016 – January 10, 2017
Statistical Regression analysis of the diamonds dataset.
View Projectwines-data-analysis
December 19, 2016 – February 4, 2017
Results of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars
View Projecthousing-sales-tseries
December 15, 2016 – January 9, 2017
Modeling the new housing approvals in Spain from 1997 to 2013 as a time series in R.
View Projectspark-flights-delay
November 7, 2016 – December 26, 2016
Predicting the arrival delay of US commercial flights using Spark and MLlib.
View Projectstorm-kafka-twitter
November 5, 2016 – December 26, 2016
Scan Twitter trending topics in a distributed environment using Apache Kafka and Storm.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal projects, indicating self-motivation and a passion for data science. The diversity of projects, from web scraping to neural networks and big data, suggests adaptability and a broad interest in the field. However, the lack of team-based or professional projects (outside of the current role with no details) makes it difficult to fully assess cultural fit in a collaborative environment. The current role as 'Data Scientist' at Cabify aligns well with the target role, but without details on responsibilities or achievements, the depth of this fit is unclear.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style.