описание
Agrobank is Uzbekistan’s 2nd largest bank by assets and the country’s leading lender to agriculture, from small farms to large agribusinesses. We’re building a new Analytics Center, and we’re looking for a Risk Analyst who wants to help the bank see problems before they happen and recover more when they do. This role goes beyond calculating NPL at month-end. You’ll build the early warning signals, analyze how well collection works, find what drives loan quality, and give the risk team data they can trust.
задачи
- Analyze the credit portfolio: retail, SME, corporate and agricultural loans
- Build vintage analysis, roll rates and delinquency buckets to spot deterioration early
- Create early warning indicators and alerts for portfolio risk
- Analyze collection performance: cure rates, recovery rates and effectiveness by stage, from soft collection to court
- Help segment overdue clients and measure which collection strategies work best
- Prepare data for IFRS 9 provisioning and regulatory reporting
- Agree on risk metric definitions with Risk, Finance and the business, and document them
- Check data quality and reconcile risk figures against accounting
- Use AI agents to automate routine checks and reports
требования
- 3+ years in credit risk, collections, or risk analytics in banking or fintech
- Understanding of credit risk: NPL, PD, LGD, EAD, expected loss, restructuring
- Understanding of collection metrics: cure rate, recovery rate, roll rate
- Strong SQL: complex queries, window functions, large datasets
- Python for analysis and automation
- BI: DataLens or similar tools
- Git: branches, pull requests, code reviews
- Ability to explain risk findings clearly to management
- Uzbek and Russian languages
- Будет плюсом: Experience with IFRS 9 or Central Bank of Uzbekistan risk reporting; Agricultural or SME lending experience; Statistics and scoring model basics; Hands-on work with AI agents: MCP, SKILL.md / AGENTS.md / CLAUDE.md
условия
- A unique portfolio: agricultural lending brings risks you won’t see in a typical retail bank
- Data Engineering and System Analytics teams are already in place
- Build risk and collection analytics from the ground up and set the standards
- It’s a large bank with real bureaucracy, so we need someone ready to lead change and push ideas through
