Intern Classic Data Scientist

Intern Data Scientist at Sberbank's Wealth Management team, developing ML models on a large B2C/B2B client base to offer investment, insurance, and savings products.

We work on: - Recommendation systems and classification, regression, clustering models for SberBank Online and SberInvestments. - Advanced classical ML approaches (uplift modeling, imbalanced classes, feature engineering on big data, SOTA algorithms) Responsibilities: - Research data, develop new informative features, and add new sources to the team pipeline. - Build ML models based on various data: tabular, event sequences (clickstream, transactions, etc.) - Implement modules of the team's development framework to increase DS productivity and improve code quality in a production environment.

Knowledge of classical ML algorithms (linear models, metric algorithms, gradient boosting) and their application to regression, classification, and ranking tasks - Solid SQL skills - Excellent Python knowledge, including libraries: catboost, pandas, numpy, sklearn Will be a plus: - Experience building uplift models - Experience solving real business problems - Understanding of PySpark principles and details

Office-based work format - Modern IT office near Moscow City with a fitness center - Favorable mortgage and credit terms for employees - Free SberPrime+ subscription - Discounts on partner company products - Medical insurance from day one and preferential insurance for family - Corporate pension program - Company-paid training: online courses in Sber's online school, unlimited library access, training at the Corporate University, workshops, meetups, opportunity to get new qualifications - Largest DS&AI Community: over 600 bank DS professionals, regular knowledge exchange, interactive lectures and masterclasses from leading universities and tech companies, digest on latest DS&AI developments, and reports from major world conferences