Adriano Yoshino
Senior Data Scientist
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAdriano Yoshino is a Senior Data Scientist with nine years of experience applying machine learning, causal inference, and NLP across retail, ad-tech, financial services and healthcare, currently at Harvard Business School. He blends a business-oriented, hacker mindset with strong production skills—building data visualization web apps and dashboards using tools from R Shiny and Plotly Dash to Tableau and Superset to drive measurable outcomes. His background spans end-to-end probabilistic modeling and experimentation, including lead roles delivering Bayesian and production ML systems at Fulcrum Analytics and Thomson Reuters Labs. An active open-source contributor, he implemented and tested inverse CDFs for multiple distributions in the widely used PyMC probabilistic programming library, reflecting deep numerical and statistical expertise. He teaches practical dashboard development on his YouTube channel and is fluent in English and Portuguese, bringing cross-cultural perspective from work in Brazil and the U.S. Known for turning complex analyses into clear visual stories, he pairs technical rigor with product-focused impact.
9 years of coding experience
9 years of employment as a software developer
Master's degree Applied Urban Science and Informatics, Master's degree Applied Urban Science and Informatics at New York UniversityBachelor of Engineering (BEng) Civil Engineering, Bachelor of Engineering (BEng) Civil Engineering at USP - Universidade de São Paulo
Portuguese, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
statistics10
mcmc10
pymc10
probabilistic-programming10
python10
statistic10
bayesian-inference10
numpy9
testing9
Programming languages (2)
Github contributions (5)
pymc-devs/pymc
Dec 2021 - Dec 2021
Bayesian Modeling and Probabilistic Programming in Python
Role in this project:
Data Scientist
Data ScientistContributions:24 reviews, 1 commit, 8 PRs in 1 day
Contributions summary:Adriano primarily contributed to the implementation of inverse cumulative distribution functions (ICDF) for various statistical distributions within the PyMC library. Their work focused on adding and testing ICDF functions for continuous distributions such as Cauchy, Logistic, Lognormal, and others. They also updated test suites to ensure the correctness of the implemented functions, demonstrating a strong understanding of probability distributions and numerical methods.
pythonbayesian-inferencestatistical-inferencemachine-learningprobabilistic-programming
amyoshino/pymc
Dec 2021 - Mar 2024
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
Contributions:74 pushes, 15 branches in 2 years 4 months
pythonmachine-learningprobabilistic-programmingbayesian-statisticsprobabilistic-machine-learning
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