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Tier-1 bank, metro location, and broad technical/tool requirements increase candidate competition.
Role requires finance-specific modeling knowledge and SDLC experience, limiting cross-industry transferability.
Explicit 2+ years, domain-specific model-ops experience, and mandatory tech stack increase screening rigor.
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Participate in and assist with low to moderately complex quantitative model maintenance, optimization, testing, implementation, and documentation.
Analyze data sets and model outputs to validate model efficiency supporting business opportunities.
Develop and present recommendations on model optimization methodology to leadership while collaborating across teams.
2+ years of quantitative model solutions or operations experience (via work experience, training, military, education).
Bachelor's degree in finance, statistics, computer science, IT, or related field with 2+ years relevant experience.
Experience with Python/R or SAS, Excel, data visualization tools (PowerBI/Tableau/Qlikview), SQL, and database testing.
Experience in finance/credit/banking modeling and understanding of industry-specific SDLC processes.
Experience working with finance/credit modeling teams and domain-specific testing requirements.
Demonstrated ability to develop automated testing frameworks and handle large data volumes efficiently.
Capable of working in complex organizations with global teams and presenting solutions to leadership.