Hi, I'm Renan!

...just a guy fascinated with Statistics and Data Science

About Me

I'm currently working as a Data Science Analyst at Agibank in Porto Alegre, Brazil, engaging in Data Science projects. My main interests comprises data analysis, data visualization, statistical modelling, open-source technologies (R, Python, Shiny, RStudio, Jupyter Notebooks, etc.), software development and Big Data.

I recently worked as a Postdoctoral Scholar at the Center for Geospatial Sciences at the University of California, campus Riverside (UCR). In this experience, I worked under the supervision of Serge Rey and the research involved developing new methods of inference for nonspatial and spatial segregation measures, new methods for identifying and dealing with neighborhoods, spatial interpolation methods, and data visualization for spatial data. I'm also a Core Developer of the Python Spatial Analysis Library (PySAL).

I earned a Ph.D. in Economics from the Pontifical Catholic University of Rio Grande do Sul (2017) (with Honorable Mention), a Master's in Statistics from the Federal University of Minas Gerais (2014) and a Bachelor's in Statistics from the Federal University of Rio Grande do Sul (2010). Besides my academic career, I also worked as a researcher in statistics at the Statistics and Economics Foundation in southern Brazil for eight years and was a professor of Data Analysis with R at the Data Science and Big Data post-graduation of UniRitter university.


Postdoctoral Scholar

  • 2018 – 2019
  • University of California, Riverside
  • Advisor: Dr. Serge Rey
  • Activities: research focused on software development using Python for spatial data science. One of the core developers of the Python Spatial Analysis Library (PySAL).
  • My Postdoctoral Statement can be found here.



PhD in Economics (Honorable Mention Earned)

  • 2015 - 2017
  • Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
  • Ensaios em Criminalidade no Rio Grande do Sul (Essays in Criminality in Rio Grande do Sul)
  • Advisor: Dr. Adelar Fochezatto
  • Scholarship from: CAPES



Master's in Statistics



Bachelor's in Statistics



Data Science Analyst

  • 2019 – Current
  • Agibank, Porto Alegre, Brazil
  • Working in the Data Science Corporate team in the financial sector.
  • Technologies used:
    • Queries on-premise and in the Data Lake (Hive, Presto, Hue, Spark, SQL Server, Jupyter, PySpark)
    • R, Rmarkdown, Shiny, tidyverse, htmlwidgets, ShinyProxy with LDAP authentication, H2O
    • Python, pandas, pyautogui, kafka-python
    • Docker, Amazon EC2, GitLab, Jenkins, Kubernetes, Rancher



Prof. of Data Analysis with R

  • 2018 – 2018
  • UniRitter University, Porto Alegre, Brazil
  • Activities: professor of Data Analysis with the R in the Data Science and Big Data postgraduation course. The course comprised a Data Science workflow (importing data, cleaning data, wrangling, data exploring, modeling and visualizing), fundamentals of the language, the tidyverse approach, best practices of the language and how to develop reports and web applications.
  • Teaching material can be found clicking here.



Researcher in Statistics

  • 2010 – 2018
  • Statistics and Economics Foundation, Porto Alegre, Brazil
  • Activities: develop Shiny applications with public data, develop new methods for estimating international trade indexes, develop and estimate economic indicators, database manager, header of department for more than four years, presentations in press conferences, writing reports and participation in data-driven consultings for the state government of Rio Grande do Sul, Brazil.



springerQuarantineBooksR: download all Springer books made available during the COVID-19 quarantine

With the Coronavirus outbreak having an unprecedented impact on education, Springer Nature launched a global program to support learning and teaching at higher education institutions worldwide. This project is an R package that has the download_springer_book_files function which can be used to download all (or a subset) of these Springer book files freely available.

For more infomation, click here.



PySAL segregation module

This work is a development of an open-source module in the Python Spatial Analysis Library (PySAL) for nonspatial and spatial segregation measures. In urban geography and regional planning, segregation, usually consider five dimensions in a given society such as evenness, isolation, clustering, concentration and centralization. Furthermore, it also presents a novel feature that performs inference for segregation and for comparative segregation, relying on simulations under the null hypothesis.

For more infomation, click here.



tobler: a library for spatial interpolation in Python

The tobler package is a library to deal with different methods of spatial interpolation for extensive and intensive variables.

This package will be part of the harmonization layer for the Geospatial Neighborhood Analysis in Python (geosnap) package in Python. In this project, I’m working directly in different approaches to harmonize different set of variables to perform a uniform set of boundaries of any different set of divisions. The original idea of this project can be found here.

The functions can comprise areal interpolation and also auxiliary variable (such as satellite images of the National Land Cover Dataset). For more information about these methods, you can check this paper and this R package.

In addition, we are refining these methods to be executed at scale, using GeoSpark and optimized algorithms for raster data, such as the scanline.

For more information regarding this project, click here.




This work is a portal of many Shiny applications using public data of the state of Rio Grande do Sul (RS), Brazil. There are applications using crime data, demographic data, socioeconomic data (idese), quarterly GDP data and economics data related to the Business Cycle of RS.

For more infomation, click here.



List of Publications

Complete List

Main papers

  • Rey, S.; Han, S. Y.; Kang, W.; Knaap, E.; & Cortes, R. X. A Visual Analytics System for Space–Time Dynamics of Regional Income Distributions Utilizing Animated Flow Maps and Rank-based Markov Chains. Geographical Analysis (2020). Special Issue. url: https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12239. doi: 10.1111/gean.12239

  • Stefanie Lumnitz; Dani Arribas-Bell; Renan Cortes; James Gaboardi; Verena Griess; Wei Kang; Taylor Oshan; Levi Wolf; and Sergio Rey (2020). splot - visual analytics for spatial statistics. Journal of Open Source Software (2020). 5(47). url: https://doi.org/10.21105/joss.01882. doi: 10.21105/joss.01882

  • Cortes, Renan Xavier; Rey, Sergio; Knaap, Elijah, and Wolf, Levi (2020). “An open-source framework for non-spatial and spatial segregation measures: the PySAL segregation module.” Journal of Computational Social Science 3, 135–166. https://doi.org/10.1007/s42001-019-00059-3

  • Colombo, J. A., Cortes, R. X., Cruz, F. I., and Paese, L. H. (2018). Building State-Level Business Cycle Tracer Tools: Evidence from a Large Emerging Economy. International Journal of Economics and Finance, 10(5), 14.

  • Cortes, Renan Xavier, Adelar Fochezatto, and Paulo de Andrade Jacinto. “Crimes nos municípios do Rio Grande do Sul: análise a partir de um índice geral de criminalidade.” Estudos Econômicos (São Paulo) 48.3 (2018): 451-487.

  • Cortes, R. X., Martins, T. G., Prates, M. O., and Silva, B. A. (2017). Inference on dynamic models for non-Gaussian random fields using INLA. Brazilian Journal of Probability and Statistics, 31(1), 1-23.

  • de Oliveira, Lívio Luiz Soares, and Renan Xavier Cortes. “Faith and religious attendance in Brazil.” Rationality and Society 28.3 (2016): 320-334.

  • CORTES, R. X.; FOCHEZATTO, A. ; JACINTO, P. A. . Daylight Saving Time and Homicides: light effect in crimes of a Brazilian state. ANÁLISE ECONÔMICA (UFRGS), 2020. (Forthcoming)


Music & Sports

  • In most of my leisure time, I like to spend it playing my acoustic guitar.

  • I also enjoy practicing basically any kind of sport.