Alexandre Andorra
Data Scientist, Product Analytics
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAlexandre Andorra is a senior data scientist and entrepreneur with 8+ years building production probabilistic AI systems across sports analytics, pharma, and tech, currently driving product analytics and causal measurement at Meta. He co-founded PyMC Labs, scaling it from 0→$1M in two years while delivering Bayesian A/B testing, GP forecasting, and causal pipelines for Fortune 500 clients. A core contributor to PyMC and ArviZ, Alexandre has improved example notebooks and plotting utilities used by thousands of practitioners and helps grow the Bayesian community as creator of the Learn Bayesian Statistics podcast (12K monthly listeners). He pairs rigorous academic grounding (HEC Paris, Freie Universität Berlin, Stanford coursework) with hands-on production experience—e.g., forecasting models that informed $100M+ roster decisions for the Miami Marlins. Fluent in English, French, and Spanish, he also monetized education—$100K+ revenue training 200+ students—demonstrating rare fluency translating advanced Bayesian methods into business impact.
7 years of coding experience
5 years of employment as a software developer
Technology Entrepreneurship and Entrepreneurial Communication, Technology Entrepreneurship and Entrepreneurial Communication at Stanford UniversityMaster of Science - MSc, Public Policy, Master of Science - MSc, Public Policy at Freie Universität BerlinMOOC, Python Development, MOOC, Python Development at Python for Entrepreneurs - TalkPython TrainingMaster of Science - MSc, Management, Master of Science - MSc, Management at HEC ParisMOOC, Data Science, MOOC, Data Science at Python Data Scientist - DataCamp
French, English, German, Spanish
Github Skills (18)
bayesian-statistics10
probabilistic-programming10
python10
statistics10
exploratory-data-analysis10
statistic10
numpy10
mcmc10
arviz10
pymc10
bayesian10
statistical-models10
jupyter-notebook10
bayesian-inference10
data-analysis10
Programming languages (6)
Github contributions (5)
pymc-devs/pymc-resources
Jun 2019 - Jul 2020
PyMC educational resources
Role in this project:
Data Scientist
Data ScientistContributions:20 reviews, 15 commits, 37 PRs in 1 year 1 month
Contributions summary:Alexandre contributed answers and solutions to the end-of-chapter practice problems, focusing on Bayesian inference and statistical modeling within the PyMC3 framework. Their work included implementing and analyzing various statistical models, demonstrating a solid understanding of Bayesian methods. The user's contributions were primarily centered on applying Bayesian techniques to a range of problems, including binomial and Poisson regressions. The user also performed checks and updated plots within the notebooks, showing engagement with the educational material.
pymcbayesian-inferencebayesian-statisticsdata-sciencedata-analysis
pymc-devs/pymc
Jan 2020 - Oct 2022
Bayesian Modeling and Probabilistic Programming in Python
Role in this project:Data Scientist
Data ScientistContributions:1 release, 323 reviews, 31 commits in 2 years 9 months
Contributions summary:Alexandre made substantial contributions to the PyMC repository, focusing on example notebooks and code related to Bayesian modeling and probabilistic programming. Their commits updated and improved several notebooks, including those for the radon example, posterior predictive checks, and the Mauna Loa example. These updates involved code cleanup, typo fixes, modifications to sampling defaults, and improvements to the overall presentation and functionality of the examples, demonstrating a focus on model validation and practical application.
bayesianprobabilistic-programmingpythonstatistical-analysisbayesian-inference
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