Ian Castillo
DataOps Lead, Global BizOps
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolIan Castillo is a DataOps leader and analytics-engineering strategist with 11 years of experience building data products and ML-enabled decision systems across operations and fintech. Currently leading Global BizOps DataOps at Uber after senior data science roles driving large-scale projects like LatAm Uber Pro and automated rider segmentation, he blends hands-on pipeline design with cross-functional program leadership. Previously at Nubank he helped design a credit acquisition model that scaled customer growth by 30% month-over-month while preserving risk, demonstrating a rare mix of commercial impact and rigorous risk control. Trained in actuarial science and applied probability, he brings formal quantitative depth from UNAM and CIMAT into practical AI and analytics engineering. An active technical writer on causal inference documentation, he focuses on making complex methods accessible to product and operations teams.
11 years of coding experience
7 years of employment as a software developer
Diploma in Big Data as Business Strategy Business Statistics, Diploma in Big Data as Business Strategy Business Statistics at Tecnológico de MonterreyUniversidad Nacional Autónoma de México (UNAM)
English
Github Skills (3)
causal-inference10
documentation10
python4
Programming languages (3)
Github contributions (5)
matheusfacure/python-causality-handbook
Apr 2022 - Aug 2022
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Role in this project:
Technical Writer
Technical WriterContributions:2 reviews, 5 commits, 7 PRs in 3 months
Contributions summary:Ian primarily focused on improving the writing style and clarity of the project's documentation. Their commits involved reviewing chapters with Grammarly, suggesting and implementing modifications to enhance the text's readability. The changes included correcting grammatical errors, adding missing letters, and modifying the overall presentation of the content. The user's efforts aimed to refine the documentation, making the technical concepts more accessible to readers.
pythoncausalbraverigorousstatistics
donelianc/introduccion-inferencia-causal
Apr 2022 - Jul 2022
Inferencia causal para los valientes y verdaderos. Un enfoque ligero pero riguroso para aprender sobre la estimación causal y el análisis de sensibilidad.
Contributions:41 commits, 5 PRs, 41 pushes in 3 months
statisticsloscausalsobreaprender
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