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# Data Scientist for Machine Learning Team

- **Company:** Smadex
- **Location:** Barcelona, Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Data Analysis, Artificial Neural Networks, Program Optimization, Game Theory, Graph Theory, Monitoring of Systems, Python (Programming Language), Machine Learning, SQL Databases, Information Technology, Xgboost, Drilldown
- **Published:** August 15, 2026
- **Apply:** https://es.trabajo.org/oferta-4021-e36b42c642485c00a975a18559e26c7b

## About the Role

"black box" implementations. - Experimentation: Design and analyze experiments, A/B testing, to validate hypotheses regarding bidding strategies and model improvements. - System Optimization: Identify performance bottlenecks and propose architectural or feature enhancements to resolve non-optimal performance at the system level. What are we looking for - Educational Background: A strong fundamental education (BSc, MSc, or PhD) in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or Data Science. - Technical Stack: Python, SQL. - Statistical Rigor: A deep understanding of Statistics and Probability theory. - ML Knowledge: Familiarity with core ML architectures - Gradient Boosting, Deep Neural Networks. Bonus Points (highly valued): - Knowledge of Game Theory (auction dynamics). - Background in Statistical Physics. - Experience with Bayesian Inference. - Discrete maths and graph theory Please note that we do NOT provide VISA

## Description

reality. You will be the analytical anchor dedicated to ensuring the performance and stability of our core models (Deep Neural Networks and Gradient Boosting decision trees) within our high-frequency, complex auction ecosystem with millions of ad requests processed every second. We are looking for a deeply analytical individual-someone who isn't satisfied with "it works," but needs to understand the system at a fundamental level. You will apply scientific rigor to drive measurable improvements in our live bidding performance. Your Tasks and Responsibilities - Deep-Dive Analysis: Conduct in-depth analysis of algorithms behavior in the live auctioned environment to understand how our algorithms interact with market dynamics. - Model monitoring tools: Collaborate on the development and automation of advanced model performance monitoring tools. Understand our ML models in production. Develop tooling that helps the team understand why the models make specific predictions, moving beyond


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