Cristian Martinez
Data Science Manager
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolCristian Martinez is a Data Science Manager based in Berlin with 10 years of experience building production-ready ML solutions and leading analytics teams at OLX Group. He progressed through hands-on roles from Data Scientist to Lead Data Scientist and now manages data science strategy and delivery, blending expertise in machine learning, deep learning, and software engineering (Python, Java, C++). His background includes applied NLP, churn and LTV modeling, A/B testing, and fraud detection with measurable results in high-precision classifiers for major clients. Cristian contributes to practical MLOps education, improving experiment-tracking notebooks in the popular DataTalksClub/mlops-zoomcamp repository and demonstrating proficiency with MLflow and XGBoost. He combines research instincts from early R&D roles with a product-focused mindset, partnering closely with product, design, and marketing teams to turn models into business impact. Known for driving reproducible ML workflows and clear evaluation practices, he brings both technical depth and operational rigor to scaling data science.
10 years of coding experience
9 years of employment as a software developer
Licenciado en Ciencias de la Computación, Computer Science, Licenciado en Ciencias de la Computación, Computer Science at University of Buenos Aires
Spanish, English, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (12)
scikit10
scikit-learn10
xgboost10
mlflow10
python10
machine-learning9
data-monitoring8
uptime-monitoring8
process-monitoring8
monitoring8
performance-monitoring8
pandas7
Programming languages (2)
Github contributions (5)
DataTalksClub/mlops-zoomcamp
May 2022 - Jun 2022
Free MLOps course from DataTalks.Club
Role in this project:
ML Engineer
ML EngineerContributions:13 commits, 7 pushes, 1 branch in 17 days
Contributions summary:Cristian primarily contributed to the development and improvement of an experiment tracking notebook within the MLOps Zoomcamp repository. They added new versions of the notebook, incorporating code changes related to experiment tracking, potentially including logging metrics, parameters, and models. Based on the code differences, the user demonstrated skills in using MLflow for model management and logging artifacts, specifically focusing on XGBoost and potentially other scikit-learn models like Random Forest Regressor and LinearSVR. The contributions appear geared towards practical application of MLOps principles within the context of model training and evaluation.
data-sciencemodel-deploymentmachine-learningmlopsmodel-monitoring
mac2bua/ai-driving-theory-teacher
Aug 2024 - Nov 2024
Contributions:18 pushes, 1 branch in 2 months
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