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Tier-1 brand, metro location, and mid-level experience create high applicant competition.
Role requires finance-modeling, risk/compliance and model-testing expertise, so cross-industry transferability is low (high sensitivity).
Explicit 4+ years, mandatory finance-modeling domain and specific tech stack make shortlisting highly strict.
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Lead or participate in model maintenance, optimization, and validation initiatives related to operating processes, controls, reporting, testing, implementation, and documentation.
Analyze quantitative models and data to validate efficiency and support business initiatives, providing advisory on model optimization and process strategies.
Independently resolve moderately complex issues, lead teams to meet project deliverables, and collaborate with global teams to achieve goals.
4+ years of quantitative solutions engineering, model solutions, or quantitative model operations experience.
Bachelor’s degree in finance, statistics, computer science, Information Technology, or a related field.
Experience with Python/R or SAS, Excel, and data visualization tools such as PowerBI, Tableau, or Qlikview.
Experience in finance/credit/banking modeling and strong understanding of industry-specific SDLC processes.
Experienced in handling large volumes of data with strong data engineering, analysis, and database testing skills including SQL query writing.
Track record of implementing automated testing frameworks in Python using Pytest or Selenium and involvement in platform migration or model reengineering projects within the finance sector.
Ability to partner effectively with business and finance/credit modeling teams, navigating complex organizations and compliance requirements to deliver innovative solutions.