We are the "Collection Strategies" team within the "Risks" department, handling a wide range of tasks related to optimizing Pre-collection and recovery strategies, and improving the efficiency of existing processes.
Our goal is to use statistics and analytics to identify the fastest and most effective way for a client to resolve difficulties with servicing their credit debt.
You will have the opportunity to analyze the largest retail portfolio in the Russian Federation, formulate hypotheses for research, launch A/B tests, evaluate effects, identify growth areas, and implement proposals aimed at increasing the effectiveness of recovery and Pre-collection strategies.
Your responsibilities will include:
- forming hypotheses to improve the efficiency of the recovery process, organizing their testing, and preparing conclusions and proposals for changes to risk strategies
- developing proposals for improving the logic, and advancing the technological tools for applying risk strategies/models and their interaction with external sources
- interacting with business units to defend changes, pilot results, system enhancements, and projects
- developing and maintaining portfolio and operational reporting
- searching for, researching, analyzing, and piloting new tools and best practices in recovery processes (social networks, big data, machine learning)
- portfolio risk management of the retail credit portfolio in terms of recovery, launching and adjusting procedures for automatic multifactor analysis of the early collection portfolio
- ensuring that business plan performance indicators meet target values, and identifying the causes of deviations
- ability to find solutions for complex analytical cases in portfolio analysis, and conducting backtesting of models to improve strategies.
We expect from the candidate:
- higher education (physics/mathematics/technical)
- advanced knowledge of SQL, Greenplum (ability to write complex queries and optimize SQL code), Python
- experience in solving complex analytical tasks, and skills in working with large datasets;
Will be a plus:
- experience working in a bank's risk department / collection departments / collection agency
- experience in developing and automating customer interaction strategies, developing business requirements, testing, and accepting new system functionality
- experience in supporting machine learning models throughout their entire lifecycle, including interaction with technical teams (DE, DS, Dev).
We offer:
- a comfortable modern office near Kutuzovskaya metro station
- office-based work format
- annual salary review
- corporate gym and recreation areas
- over 400 educational programs from SberUniversity for professional and career development
- adaptation program and supervisor support at the start (for Junior positions)
- extended VHI (Voluntary Health Insurance), preferential insurance for family, and corporate pension program
- a flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- Prime subscription with the possibility of shared use with three close individuals
- reward for recommending friends to the Sber team.
