Analyst for the Financial Analytics Team in Fintech

We, in the financial analytics team, create and develop high-load systems for forecasting, risk analysis, and regulatory reporting. One of our areas of work is analytical support for the treasury, which helps the business effectively place free funds, manage risks, and comply with all regulatory requirements.

We are looking for a person who will automate the calculation of key banking prudential ratios, model ALM risks (liquidity and interest rate risk), and build analytical reports. Your work will ensure the reliability, transparency, and efficiency of processes critical to the bank's stability and will have a real impact on the business.

What tasks await you

Automation of prudential and risk calculations You will be responsible for developing, implementing, and maintaining automated systems for calculating mandatory prudential ratios (liquidity, capital) and ALM indicators (structural gap, NII/NIM simulation). You will ensure that calculation methodologies comply with the requirements of the Central Bank of the Russian Federation and create the infrastructure for regular (daily and monthly) operational calculations.

Development of analytical reports and visualizations You will create intuitive dashboards and reports to present calculation results to management and business users, as well as automate the generation of regular reporting for internal and regulatory needs.

Full cycle of analytical solution development You will be involved in the entire process: from analyzing requirements and data to designing, writing code, testing, and deploying scripts and services into production. You will also optimize and maintain calculation processes, improving their efficiency and reliability.

Learn more about analytics at Yandex — in the channel Yandex for Analytics

We expect you to have

• A higher technical, mathematical, or economic education (mathematics, CS, physics, engineering, economics, finance)
• Proficiency in Python for data analysis and automation (Pandas, NumPy, SciPy)
• Understanding of the principles of clean, efficient, and testable code
• Proficiency in SQL, with experience writing complex queries for working with large data volumes
• Understanding of the fundamentals of banking risk management, especially liquidity and interest rate risk
• An analytical mindset, attention to detail, and a drive to automate routine operations

Will be a plus

• Experience working in credit institutions (banks) in treasury, risk management (ALM, market risk), financial modeling, mandatory reporting, or financial analytics departments
• Experience with banking reporting automation systems
• Experience independently building an analytical process (requesting and collecting data, developing and implementing models, BI visualization of results)
• Experience automating analytical processes using ML or LLM