About Me



I'm currently working as a Data Science Specialist at Sicredi, a Brazilian financial instituton with 5+ million costumers. Previously, I was a Data Science Corporate Leader 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.

During 2018-2019, I 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.


Education


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.

 

Education


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

 

Education


Master's in Statistics

 

Education


Bachelor's in Statistics

* __2006 - 2010__ * Federal University of Rio Grande do Sul, Porto Alegre, Brazil * [Um estudo comparativo de estimadores de regressões não-paramétricas aditivas: Performance em Amostras Finitas](https://lume.ufrgs.br/bitstream/handle/10183/24871/000749685.pdf?sequence=1&isAllowed=y){:target="_blank"} (*A comparative study of non-parametric additive regression estimators: Finite Sample Performance*) * Advisor: [Dr. Fernando Augusto Boeira Sabino da Silva](https://www.linkedin.com/in/fernando-b-sabino-da-silva-ph-d-73b05ab1/)

 

Experiences


Data Science Specialist

* __2022 – Current__ * Sicredi, Porto Alegre, Brazil * Working in the Data Science Corporate team in the financial sector. * Technologies used: + R, Python, Jupyter, Docker, Jenkins, Kafka, MongoDB, PostGres, Amazon Athena, MLFlow + H2O, Multi-Armed Bandits (ε-Greedy, Upper Confidence Bound, Thompson Sampling)

 

Experiences


Data Science Corporate Leader

* __2019 – 2022__ * 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, FastAPI, Selenium + Docker, Amazon EC2, GitLab, Jenkins, Kubernetes, Rancher

 

Experiences


Invited Professor of Data Science and Artificial Intelligence Specialization

* __2020 – 2020__ * PUCRS University, Porto Alegre, Brazil * PUCRS Online is an innovative initiative of PUCRS that depicts many courses that mix professors from the university and names from the market. The objective is to give to the student a broader perspective of the field of each course. * As an invited professor of the PUCRS specialization online course of Data Science and Artificial Intelligence, I was responsible for the "Data Science and Artificial Intelligence Introduction" course from the market perspective. I focused on my personal Data Science experiences, use-cases, job market, state-of-art methodologies, daily workflow, and, at last, an end-to-end Data Science pipeline with hands-on experience in R, ranging from importing, tidying, wrangling, visualizing, and modeling. * The class was recorded and will be part of the course.

 

Experiences


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**](https://github.com/renanxcortes/data_analysis_with_R_teaching_material){:target="_blank"}.

 

Experiences


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.

 

Projects


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**](https://github.com/renanxcortes/springerQuarantineBooksR){:target="_blank"}.

 

Projects


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**](https://github.com/pysal/segregation){:target="_blank"}.

 

Projects


tobler: a library for spatial interpolation in Python

The [**tobler**]((https://github.com/spatialucr/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**](https://github.com/spatialucr/geosnap){:target="_blank"} (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**](http://conference.scipy.org/proceedings/scipy2018/pdfs/serge_rey.pdf){:target="_blank"}. 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**](https://www.researchgate.net/publication/5153750_Areal_Interpolation_of_Population_Counts_Using_Pre-Classified_Land_Cover_Data){:target="_blank"} and [**this R package**](https://cran.r-project.org/web/packages/areal/vignettes/areal.html){:target="_blank"}. In addition, we are refining these methods to be executed at scale, using [**GeoSpark**](https://github.com/DataSystemsLab/GeoSpark){:target="_blank"} and [**optimized algorithms for raster data, such as the scanline**](https://www.researchgate.net/publication/328949782_Distributed_zonal_statistics_of_big_raster_and_vector_data){:target="_blank"}. For more information regarding this project, click [**here**](https://github.com/spatialucr/tobler).

 

Projects


VisualizaFEE

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**](https://github.com/renanxcortes/VisualizaFEE){:target="_blank"}.

 

Publications


List of Publications

### Complete List - [GoogleScholar](https://scholar.google.com/citations?user=gNOcE4AAAAAJ&hl=en) ### Main papers - Cortes, Renan Xavier, Adelar Fochezatto, and Paulo de Andrade Jacinto. "Daylight Saving Time and Homicides: Light Effect in Crimes of a Brazilian State." *Análise Econômica (UFRGS)* 39.79 (2021). url: https://seer.ufrgs.br/AnaliseEconomica/article/view/80052/63415 - Sergio J. Rey, Luc Anselin, Pedro Amaral, Dani Arribas-Bel, Renan Xavier Cortes, James David Gaboardi, Wei Kang, Elijah Knaap, Ziqi Li, Stefanie Lumnitz, Taylor M. Oshan, Hu Shao, Levi John Wolf (2021). "The PySAL Ecosystem: Philosophy and Implementation." *Geographical Analysis.*. URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12276 - Rey, Sergio Joseph, Renan Cortes, and Elijah Knaap. "Comparative Spatial Segregation Analytics." Spatial Demography (2021): 1-26. url: https://link.springer.com/article/10.1007/s40980-021-00075-w - 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.

Hobbies


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.