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Tier-1 bank, metro location, and mid-level generalist profile drive high candidate competition.
Role demands banking capital and credit-risk expertise, reducing cross-industry transferability.
Explicit Python/C++ requirement, quantitative skills and regulatory knowledge create stringent filtering.
Develop and maintain quantitative analytics and forecasting tools for capital, expected credit loss, financial resource management, and performance decision-making.
Translate business and regulatory requirements into scalable implementations primarily using Python and C++, ensuring control, data quality, and documentation standards.
Collaborate with global Front Office, Credit Risk Management, Finance, and Technology teams to gather requirements, resolve issues, and deliver agreed outcomes.
Strong academic background in quantitative disciplines such as engineering, computer science, mathematics, statistics, physics, finance, or economics.
At least two years of hands-on Python development experience including data analysis and production-quality coding.
Working knowledge of C++ concepts including object-oriented programming and common data structures.
Experience with relational databases and SQL; preferred knowledge of database design using Oracle or MySQL.
Demonstrated ability to work across business, risk, finance, and technology teams globally, managing competing priorities and delivering in fast-moving environments.
Strong quantitative foundations with practical exposure to banking products, credit risk, regulatory capital, expected credit loss, or financial resource management.
Proven experience in structured problem-solving, ownership of data quality and controls, and explaining quantitative topics to varied stakeholders.