Portfolio Analyst

We’re looking for a Portfolio Analyst to help us scale and optimize our credit portfolio. You’ll work hands-on with portfolio metrics, risk strategies, and pricing, collaborating closely with Product and Data Science to turn data into clear, impactful decisions. The scope of responsibilities will include:

Credit Portfolio Management:

• Analysis and monitoring of key portfolio metrics: FPD, PD, LGD, NPL, Surplus;
• LTV assessment and active participation in product pricing;
• Development of customer segmentation strategies (e.g., by risk levels, products, acquisition channels);
• Assessment of the impact of internal initiatives on financial results;
• Optimization of the portfolio structure (balancing high-yield and low-risk loans).

Risk Management:

• Monitoring of risk concentration (e.g., by regions, products, borrower segments);
• Adjustment of credit policy based on default and early repayment data;
• Development and improvement of processes related to loan origination.

Collaboration with the Data Science Team:

• Formulation of requirements for scoring models (e.g., calibration of PD models);
• Analysis of scoring card performance and proposals for their improvement;
• Work with cash flow forecasting models.

We’re looking for a Portfolio Analyst to help us scale and optimize our credit portfolio. You’ll work hands-on with portfolio metrics, risk strategies, and pricing, collaborating closely with Product and Data Science to turn data into clear, impactful ...

• 3+ years of experience in analytics or portfolio analytics;
• Higher education, preferably in a technical or economics-related field;
• Strong understanding of credit risks and metrics: PD, NPL, FPD, SPD, Roll Rate, CoR;
• Knowledge and practical application of probability theory and mathematical statistics;
• Proficiency with analytical tools:
• Excel (advanced formulas, pivot tables);
• SQL (window functions, subqueries);
• Experience working with Python (basic level: NumPy, pandas, scikit-learn);
• Knowledge of regulatory requirements applicable to MFIs/Banks.

Nice to Have:

• Experience with Big Data and BI systems;
• Basic understanding of ML models (interpretation of scoring results);
• Knowledge of financial models and statements (NPV, DCF, P&L);
• Experience with A/B testing;
• Knowledge of MFI/Banking products: microloans, credit cards, credit lines.