Description
The Corporate Risk Modeling Center is looking for an experienced leader in the field of Data Science.
Our team is engaged in building advanced models that optimize corporate lending processes, developing products for internal clients using a modern technology stack.
Our models are a driver for increasing the Bank's profit and market share, transforming credit processes.
A large volume of information of different natures and modalities (sequences, tabular data, text, etc.) combined with a developed technical infrastructure allows us to develop a wide range of models from classical algorithms to the most modern state-of-the-art models.
Responsibilities
- lead the DS team in the modeling direction for credit customer assessment in the SME segment (Micro, Small, and Medium Business)
- manage the team's backlog, ensure task prioritization and achievement of goals
- jointly with business units, formulate the development strategy for model solutions and their integration into the Bank's credit processes
- oversee the full model lifecycle: problem definition, data collection and analysis, development, implementation, and subsequent quality monitoring
n* develop the model landscape for the direction, implement modern machine learning approaches and technologies
- assess the business and financial impact of AI initiatives, validate results within pilot projects and production solutions.
Requirements
- higher education in the field of technical or physical and mathematical sciences
- experience in developing ML models and successfully managing full-cycle cross-functional projects — from idea to production — of at least 5 years
- experience in portfolio management and decision-making at the credit portfolio level
- deep knowledge of key machine learning methods, validation principles, metrics, and regularization
- confident command of modern ML/DL frameworks
- confident data skills: proficiency in SQL, query optimization, experience with distributed data processing (PySpark/Spark)
- high level of independence and responsibility, ability to conduct research, formulate hypotheses, and bring them to a measurable result.
Will be a plus
- knowledge of the basics of risk management in a Bank
- experience working with the corporate client segment in at least one of the following areas: structure of financial reporting, regulatory restrictions from the Central Bank, combating fraud schemes, portfolio risk management
- understanding of transformer architectures, tokenization, and language modeling training
- experience with generative models and LLMs — usage, adaptation of base models, continued pre-training, SFT, inference; experience in creating AI agents
- experience in developing neural networks for working with sequential data.
Conditions
- comfortable modern office: Moscow, Kutuzovsky Prospekt metro station
- work format– office-based
- annual salary review, annual bonus
- corporate gym and rest zones
- more than 400 educational programs from SberUniversity for professional and career development
- adaptation program and supervisor assistance at the start
- extended VHI (voluntary health insurance), preferential insurance for family
- mortgage for employees
- free SberPrime+ subscription, discounts on products from partner companies
- referral bonus for recommending friends to the Sber team.
