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Tier-1 brand, metro location, mid-level ML role with broad skillset increases competition.
Strong finance/credit modelling and regulatory risk focus reduces cross-industry transferability.
Explicit 2+ years plus mandatory finance modelling, Python, automation, testing and SQL skills raise strictness.
Support entry-level to moderately complex quantitative model maintenance, optimization, and validation initiatives.
Apply GenAI, ML, and automation to enhance code conversion, data quality checks, anomaly detection, and workflow optimization in finance/credit modeling.
Develop and maintain automated test scripts and frameworks ensuring data accuracy during platform migration and model reengineering projects.
2+ years experience in quantitative model solutions or model operations (or equivalent via training, education, military).
Bachelor’s degree in finance, statistics, computer science, IT, or related field with 2+ years of relevant experience.
Experience with Python/R or SAS, Excel, SQL, and data visualization tools like PowerBI/Tableau/Qlikview.
Experience in Finance/Credit/Banking modeling and understanding of SDLC processes required.
Experience executing finance sector platform migration or model reengineering projects with a strong focus on automation and testing.
Skilled in data engineering, quantitative model operations, and implementing automated testing frameworks using Python (Pytest, Selenium).
Ability to collaborate with global, cross-functional teams and translate domain-specific testing requirements into effective solutions.