Juan Camargo
Data Science Manager
Puebla City, Puebla, Mexico
Summary
👤
Senior🎓
Top SchoolJuan Camargo is a Data Science Manager and AWS Solutions Architect with 9 years of experience building and scaling Big Data products that drive measurable business impact. He specializes in geospatial intelligence, MLOps, and statistical evaluation, having designed serverless multi-cloud architectures to process 8+ TB/month of telemetry and achieve an 80% reduction in operational costs. Juan led the commercialization of a Big Data engine into a Data-as-a-Service deployed across six cities within six months and delivered performance frameworks for over 10 high-profile international initiatives (BID, ONU, Banco Mundial, FIA Foundation). He combines hands-on engineering (PySpark, Athena, Glue, S3) with product strategy and stakeholder management, negotiating large data contracts and securing strategic funding. Notably, he has transformed billions of GPS records into high-precision geospatial models (R2=0.94) and built automated video-analytics anomaly detection systems in collaboration with academia. Based in Puebla, Mexico, he brings a physics-trained analytical mindset to operationalize complex machine learning systems at scale.
9 years of coding experience
7 years of employment as a software developer
Universidad Nacional Autónoma de México (UNAM)
English, Spanish
Github Skills (134)
data-stream10
dashboard10
energy10
data-management10
thingsboard10
arduino-library10
lwm2m10
microservices10
middleware10
statistics10
chips10
wifi-configuration10
wifimanager10
iot-projects10
device-management10
Programming languages (8)
Github contributions (5)
DanielBustillos/nlp-toolkit-espanol
Aug 2020 - May 2022
Contributions:10 commits, 8 pushes, 1 branch in 1 year 8 months
DanielBustillos/Forecast-pollution-CDMX
Apr 2019 - Aug 2021
Pronosticar calidad de aire y contaminantes en la Zona Metropolitana de la Ciudad de México
Contributions:117 commits, 119 pushes, 1 branch in 2 years 4 months
forecastingxgboostairemachine-learningmetropolitana
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