Alexsandro Munhoz

Senior Solutions Architect at Itaú Unibanco

São Paulo, Brazil
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Summary

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Senior
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Top School
Alexsandro Munhoz is a Senior Solutions Architect with over two decades of experience and nine years in senior architecture and leadership roles, currently strengthening Itaú Unibanco’s technology strategy. He blends deep telecom and enterprise architecture expertise with hands-on data and AI work—having led cloud modernization, Billing 2.0, Customer 360 and RAG initiatives at Serasa Experian that cut costs and improved efficiency. Comfortable in managerial and technical capacities, he has a track record across Media, Banking, and Telco, designing systems with Salesforce, Snowflake, Databricks, Kafka ecosystems and AWS-native data platforms. Known for connecting strategic roadmaps to delivery, he also brings research rigor as a PhD-trained atmospheric physicist and former lead data scientist in agribusiness. Pragmatic and future-focused, Alexsandro builds architectures meant to endure decades while unlocking immediate business value.
code9 years of coding experience
job15 years of employment as a software developer
bookMaster of Business Administration (M.B.A.) Business Administration and Management General, Master of Business Administration (M.B.A.) Business Administration and Management General at FGV - Fundação Getulio Vargas
bookEngineer's degree MBA in Business Administration with Emphasis in Business Management, Engineer's degree MBA in Business Administration with Emphasis in Business Management at FAAP - Fundação Armando Alvares Penteado
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Github Skills (16)

unix9
multivariate-timeseries5
latex5
information-theory5
mercurial4
kaggle3
science3
data-science2
data-analysis2
sentinel2
machine-learning2
python2
git2
inference1
pandas1

Programming languages (5)

CSSShellJavaScriptJupyter NotebookPython

Github contributions (5)

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SandroAlex/phd

Feb 2022 - Jan 2023

Contributions:18 commits, 101 pushes, 1 branch in 10 months
SandroAlex/cdlearn

Oct 2019 - Nov 2023

Python package intended to manipulate and analyze climate data in the framework of Granger causality and machine learning.
Contributions:3 PRs, 48 pushes, 1 branch in 4 years 1 month
pythonclimatemachine-learninggranger-causalityclimate-data
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