Description
The 'Segments' team is a team specializing in creating ML models for analyzing customer churn, reducing transactional activity, and identifying propensities for various products. We strive to find the best solutions for business. Our team consists of six people, including graduates from prestigious universities such as MSU and HSE.
The vacant position is a cross-functional role that combines the tasks of business analysis, model building, and their industrial implementation to achieve ambitious goals.
Responsibilities
- Development and training of models for predicting customer behavior to recommend the most relevant options and services
- Analysis of various types of data (tabular data, transactional data, logs, graphs, and others) to identify patterns, root causes, and insights
- Automatic generation of hypotheses for customer retention and development
- Participation in the development and validation of business and technical hypotheses
- Creation of industrial versions of models and participation in their integration into platforms
- Evaluation of the business effects of implemented solutions
- Development and optimization of ETL pipelines for processing large volumes of data
- Industrial implementation of ML models.
Requirements
- Deep knowledge and practical experience in applying classical machine learning (ML) methods and Python programming
- Basic understanding of deep neural networks and the possibility of using them to solve business problems, especially on tabular data
- Skills in evaluating the quality of model results from the perspective of Data Science and business needs
- Advanced knowledge in the field of statistics and conducting A/B testing
- Experience with GreenPlum, PostgreSQL databases, as well as Spark and PySpark frameworks
- Confident knowledge of the main components of the Apache Hadoop ecosystem and experience with Apache Spark
- Advanced knowledge of SQL and Python; experience in industrial development and implementation of solutions from 1 year
- Experience with Python ML frameworks (Scikit-Learn, LightGBM, PyTorch, and others)
- Experience with Spark Streaming, Kafka, HBase, GreenPlum
- Experience with DevOps tools (Jenkins), Git (BitBucket)
- Experience working according to Agile methodology (SCRUM, Kanban).
Will be a plus:
- Experience in developing solutions using GenAI
- Experience in business analytics and managing DS projects
- Knowledge of Scala.
Conditions
- Comfortable modern office near Kutuzovskaya metro station
- Work format - office
- Annual salary review, annual bonus
- Corporate gym and recreation areas
- More than 400 educational programs from SberUniversity for professional and career development
- Extended voluntary health insurance (DMS), preferential insurance for family and corporate pension program
- Flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- Free SberPrime+ subscription, discounts on products from partner companies
- Reward for recommending friends to the Sber team.
