mathematical modeling, liquidity and market risk analysis, data handling with Python and SQL.
Tasks:
- Participation in the development and calibration of models for estimating the value of early loan redemption options and depositor behavior models.
- Calculation of liquidity gap and net interest margin gap indicators under various macroeconomic scenarios.
- Writing complex SQL queries and Python scripts for processing Treasury deal data.
- Automation of metrics collection from data warehouses.
- Assisting in capital and liquidity stress testing.
- Support for internal funding rate and yield curve calculations.
- Monitoring of trading portfolio positions, VaR calculation, and preparation of analytical notes.
Requirements:
- Undergraduate or Master's student at technical or financial universities.
- Knowledge of financial mathematics: time value of money, duration, convexity, derivative financial instruments.
- Understanding of the banking industry: bank balance sheet, Basel III/IV regulations, reserve requirement averaging mechanisms, money market.
- Proficiency in Python and SQL programming.
- MS Excel knowledge at the level of complex formulas and macros.
- Experience with neural networks in work is a plus.
Conditions:
- Comfortable modern office near Kutuzovskaya metro station.
- Annual salary review, annual bonus.
- Corporate gym and recreation areas.
- Sber's unique training system.
- Extended voluntary medical insurance and preferential family insurance.
- Flexible mortgage loan discount.
- Prime subscription with sharing capabilities.
- Referral bonus for recommending friends.
- Corporate pension program.
Skills:
- Python
- SQL
- Pandas
- NumPy
- MS Excel
