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Managers, Data Modeling and Analytics

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Job Description

American Express Company seeks Managers, Data Modeling and Analytics to develop, maintain, test, and. document modeling frameworks and methodologies used in asset-liability management, exposure management, and liquidity risk. Formulate various forecasting analysis, including balance, acquisition, and pricing using a variety of quantitative models and techniques. Devise and report financial data models for non-technical audiences and incorporate stakeholder feedback for leadership to formulate business. decisions. Collaborate with corporate planning modeling teams, and design and participate in firm-wide Comprehensive Capital Analysis and Review (CCAR) and Internal Capital Adequacy Process (ICAAP) stress testing. Partner with cross-functional teams, including internal validation and audit groups to address model validation findings.

Minimum Qualifications

Position requires a Master’s degree in Statistics, Mathematics, Economics, Finance, Operations Research, Engineering, or a related field, and 6 months of experience with financial data valuation techniques and derivatives pricing analysis.  Experience must include a minimum of: 6 months of experience with building statistical and financial models using large datasets; 6 months of experience with asset liability management (ALM), interest rate risk, and liquidity risk analysis; 6 months of experience with scenario analysis and comprehensive capital analysis and review stress testing; 6 months of experience with simulation, stochastic models, interest rate models, statistical modeling, and time series analysis; and 6 months of experience with Bloomberg Macros, Microsoft Excel, SAS, SQL, Tableau, and VBA.

JOB LOCATION: New York, NY

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, age, or any other status protected by law.

 


ReqID: 20008944
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Dec 10, 2020, 12:00:36 AM