Senior Data Scientist, Real-Time ML for Ad Auctions Remote

Smadex; Madrid; A distancia; EUR 60.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Private Health Insurance

LinkedIn Learning

Meal vouchers

Gym allowance

Team-building events

100% Remote within Spain

Descripción de la vacante

Smadex, a performance advertising engine for mobile apps, seeks a Data Scientist to bridge theory and production. You will work within the Machine Learning team to ensure the performance, interpretability, and stability of core Deep Neural Networks in a high-frequency auction system processing millions of ad requests per second.

You will apply rigorous ML methods, analyze live bidding dynamics, and drive measurable improvements in live performance.

Formación

• Strong background in statistics and probability applied to ML models.
• Experience designing and analyzing experiments, including A/B tests.
• Ability to translate model behavior into actionable insights for product improvements.

Responsabilidades

• Understand production ML models and explain predictions; form hypotheses and validate with data analyses.
• Conduct in-depth analysis of auction dynamics to see how algorithms interact with market dynamics.
• Design and run experiments and A/B tests to validate bidding strategies and model improvements.
• Identify bottlenecks and propose architectural or feature improvements to boost system performance.

Conocimientos

Statistical thinking

Experimentation design

Communication

DNN/ML architectures

Educación

Bachelor/Master/PhD in quantitative field

Herramientas

Python

SQL

Descripción del empleo

Smadex, a performance advertising engine for mobile apps, seeks a Data Scientist to bridge theory and production. You will work within the Machine Learning team to ensure the performance, interpretability, and stability of core Deep Neural Networks in a high-frequency auction system processing millions of ad requests per second.

You will apply rigorous ML methods, analyze live bidding dynamics, and drive measurable improvements in live performance.