The Credit Card Risk team is responsible for managing credit risk and driving profitability across the credit card portfolio. We design and implement risk decision-making processes throughout the entire customer lifecycle, including underwriting and collections strategies.
Risk strategy plays a critical role in the company’s overall performance, directly impacting growth, profitability, and portfolio quality.
Our team focuses on developing advanced analytical approaches, building models, and creating tools that enhance business processes and key metrics. We are committed to a data-driven approach to decision-making.
Challenges that await you:
- Risk and Profitability Management
- Manage, monitoring and improvement of Credit Card’s risk strategy, limit policy within adopting ML & AI models to maximise product profitability
- Develop and manage NPV model of the product
- Interaction with business department about product and origination process, product conditions, tariffs, acquisition channels profitability
- Designing, testing, and validating hypotheses to enrich knowledge about dependencies, impact of additional features, impact of changes in process
- Developing analytical frameworks and tools for fast, scalable, and comprehensive reporting
What makes you a great fit:
- 1+ year of professional experience in risk or product analytics
- Education: Mathematics, physics, engineering, economics, computer science
- Experience with databases, strong knowledge of SQL
- Experience with one of the analytical scripting languages (Python / R)
- Strong analytical skills, understanding of basic machine learning concepts
- Strong knowledge of mathematical statistics and understanding of probabilities
- B1 or higher English level for effective communication with an international team
Nice to have
- Understanding of retail risk management principles: adverse selection, vintage / portfolio analysis, knowledge of key risk and product metrics in retail lending
- Knowledge of unit economics of credit cards, ability to explain dependencies and key metrics
- Understanding of advanced machine learning concepts and approaches
- Experience working with BI tools (e.g., Tableau, Power BI, Looker, or similar)
Our ways of working:
