Minimum 5 years of experience as a Data Scientist, Strong proficiency in SQL – ability to write complex queries, join large datasets, and prepare data for modeling, Proficiency in Python (libraries such as pandas, numpy, scikit-learn, statsmodels or similar) – focus on data analysis, modeling, and result validation, Experience working with large datasets and ETL processes, Ability to work with business data and interpret analytical results, Attention to code quality and reproducibility of analyses, Expertise in the marketing and consumer analytics domain, Good understanding of segmentation models (clustering, scoring, customer profiling) and predictive models (propensity, churn, LTV), Basic knowledge of model validation and performance metrics (AUC, lift, confusion matrix)