Global Pricing ML Lead

Avolta; Madrid; Híbrido; EUR 90.000 - 130.000; Jornada completa

Descripción de la vacante

Avolta is seeking a Global Data Scientist to lead the development of advanced pricing models and production ML systems across 5,500+ locations. You will spend most of your time building models, writing production-ready code, and architecting scalable ML infrastructure, while mentoring teammates and translating insights for commercial teams.

The role requires deep expertise in pricing/revenue optimization, strong collaboration with BI engineering, and ability to communicate complex results to

Formación

• MS or PhD in quantitative field or Bachelor's with 8+ years of applied data science experience.
• Expert-level Python proficiency for data science (pandas, numpy, scikit-learn, statsmodels, scipy) with production-quality coding.
• Advanced SQL skills - complex queries (CTEs, window functions) on large datasets (100M+ rows).
• Strong foundation in statistics and econometrics: regression, hypothesis testing, causal inference, time series.

Responsabilidades

• Develop price elasticity models to estimate demand curves at SKU-category-location levels.
• Build dynamic pricing algorithms that optimize prices in near-real-time.
• Create price architecture frameworks using clustering, segmentation, and optimization techniques.
• Design margin optimization models balancing volume and profitability trade-offs.
• Build causal inference models to measure incrementality of promotions and cannibalization.

Conocimientos

Python

SQL

Pandas

Scikit-learn

Statistics

Econometrics

Data Visualization

Educación

MS or PhD in quantitative field

Bachelor + 8+ years equivalent experience

Herramientas

Airflow

Spark

Tableau

Power BI

AWS/GCP/Azure

Descripción del empleo

Avolta is seeking a Global Data Scientist to lead the development of advanced pricing models and production ML systems across 5,500+ locations. You will spend most of your time building models, writing production-ready code, and architecting scalable ML infrastructure, while mentoring teammates and translating insights for commercial teams.

The role requires deep expertise in pricing/revenue optimization, strong collaboration with BI engineering, and ability to communicate complex results to