Agustina Arroyuelo
Data Scientist Semi Senior
San Luis, San Luis, Argentina
Summary
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Rockstar🎓
Top SchoolAgustina Arroyuelo is a Data Scientist with a decade of experience combining Bayesian modeling, multilevel and non-linear regression (including Gaussian processes), and practical data engineering in Python and SQL. Currently a Semi Senior Data Scientist at Naranja X, she has a strong research background as a PhD fellow and teaching assistant in evolutionary biology, bringing rigorous experimental thinking to production analytics. An active open-source contributor and two-time Google Summer of Code participant, she contributed key visualization and circular-variable support to ArviZ and implemented an ABC module for PyMC3, work that surfaced in widely used Bayesian tooling. She routinely translates complex probabilistic models into clear visualizations and reproducible pipelines, and has a knack for adapting academic methods to business problems. Based in San Luis, Argentina, she blends deep statistical theory with hands-on implementation and library-level contributions that help other practitioners explore Bayesian models more effectively.
10 years of coding experience
3 years of employment as a software developer
Doctorado, BiologĂa, Doctorado, BiologĂa at Universidad Nacional de San Luis
Spanish, English, Japanese
Github Skills (19)
data-visualizations10
bayesian-statistics10
python10
matplotlib10
statistics10
data-visualisation10
exploratory-data-analysis10
pymc10
bayesian10
jupyter-notebook10
data-visualization10
data-analysis10
data-science9
bokeh9
k9
Programming languages (3)
Github contributions (5)
arviz-devs/arviz
Apr 2018 - Oct 2022
Exploratory analysis of Bayesian models with Python
Role in this project:
Data Scientist
Data ScientistContributions:1 release, 5 reviews, 28 commits in 4 years 6 months
Contributions summary:Agustina primarily contributed to the development and enhancement of data visualization tools within the ArviZ library. Their work included implementing a pairplot function for exploratory analysis of Bayesian models, adding features like jointplot capabilities, point estimate representation, and reference values. They also focused on improving the library's existing functionality by using a more efficient method to compute bins for density and posterior plots, and adapting summary functions for circular variables, demonstrating a focus on both improving existing plotting functionality and adding new features to ArviZ.
pythonexploratorybayesian-inferencemachine-learningbayesian-models
aloctavodia/Statistical-Rethinking-with-Python-and-PyMC3
Dec 2016 - Dec 2017
Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Role in this project:Data Scientist
Data ScientistContributions:13 commits, 19 PRs, 2 comments in 1 year
Contributions summary:Agustina primarily contributed to porting examples from the book "Statistical Rethinking A Bayesian Course with Examples in R and Stan" to Python/PyMC3. Their commits focused on implementing the examples, as evidenced by file modifications in Jupyter Notebooks, and included code changes related to the statistical models. They also addressed and fixed errors encountered in running the code, indicating their role in the project's development and refinement of the Bayesian models. The user's work included the addition of multi forestplot.
richardpythonstanstatisticalstatistical-inference
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