Sergio Pérez-lozao
Co-Founder at Bondora
Madrid, Community of Madrid, Spain
Summary
👤
Senior🎓
Top SchoolSergio Pérez-lozao is a data scientist and entrepreneur with nine years of experience building ML-driven products and teams across startups and large companies. As Co-Founder of nothiring and Lead Data Scientist at Bondora, he blends hands-on model development with MLOps expertise—MLflow, Airflow, Kubernetes and feature stores—to take experiments into production. His background spans end-to-end data work from Spark and Dask at Orange to rider acquisition and cross-company impact at Cabify, underpinned by formal training in streaming, computer vision and deep learning. Comfortable bridging research and product, he routinely explores state-of-the-art techniques and creates internal data libraries and knowledge repos to scale impact. Based in Madrid, he pairs an engineering telematics degree with a founder’s mindset, having launched multiple tech outreach projects early in his career.
9 years of coding experience
9 years of employment as a software developer
Machine Learning (Stanford University) Machine Learning, Machine Learning (Stanford University) Machine Learning at CourseraData Streaming Nanodegree, Data Streaming Nanodegree at UdacityPrograma de formación en Deep Learning (30 horas) Inteligencia artificial, Programa de formación en Deep Learning (30 horas) Inteligencia artificial at MBIT SchoolCharles III University of Madrid (Universidad Carlos III de Madrid)Programa ThePowerMBA FutureLeaders Business Expert - Gestión y Administración de Empresas, Programa ThePowerMBA FutureLeaders Business Expert - Gestión y Administración de Empresas at thePower
Spanish, English
Stackoverflow
85reputation
2kreached
0answers
4questions
Github Skills (127)
forge10
deep-learning10
relationship10
modin10
gradient-boosting10
shap10
r-package10
predict10
shapley10
machine-learning10
r9
pandas9
sql9
scale9
science9
Programming languages (8)
Github contributions (5)
sergiocalde94/pydrift
May 2020 - Sep 2021
How do we measure the degradation of a machine learning process? Why does the performance of our predictive models decrease? Maybe it is that a data source has changed (one or more variables) or maybe what changes is the relationship of these variables with the target we want to predict. `pydrift` tries to facilitate this task to the data scientist, performing this kind of checks and somehow measuring that degradation.
Contributions:23 commits, 19 PRs, 93 pushes in 1 year 4 months
data-sourcedata-sciencedegradationpredictive-modelsmachine-learning
conda-forge/pydrift-feedstock
Jun 2020 - Sep 2021
A conda-smithy repository for pydrift.
Contributions:1 review, 9 PRs, 12 pushes in 1 year 3 months
pythoncondasmithy
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