American Express is hiring a data analyst for data science operations at multiple locations and provide hybrid work option

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American express works heavily with payment data and customer spending patterns so understanding transaction analytics and credit behavior helps analysts support risk teams

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Bachelor’s or Master’s degree in Statistics, Economics, Mathematics, Engineering or any related analytical field is required 

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Work location is New York, Phoenix, AZ, Atlanta, GA and alt Lake City, UT etc. in United States with that provide hybrid work model ( Flexible Job ) 

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basic knowledge of regression models, classification methods, and clustering helps you understand customer trends, ml models support decisions around customer retention, risk scoring, and personalization

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payment companies evaluate credit risk and fraud patterns to protect customer accounts, knowing how risk scores, fraud alerts, and behavioral models work is an advantage fraud analytics is a trending high-cpc domain in the american fintech sector

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 0-5 years of experience using quantitative analysis and statistical modelling is important, means every entry level candidate can apply in Amex

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Salary Range is upto $75,000 to $1,25,000 annually with extra added bonuses & other benefits

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roles in data analytics, digital payments, credit risk, and customer science offer strong career growth,continuous learning in cloud, ai, and financial analytics opens doors to senior us-based roles that's why data domain remains one of the most stable career paths globally

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Proficiency in data manipulation and analysis using SQL, Python, R or the equivalent is important, sql is used to query large volumes of transaction records and python helps automate reporting tasks and build predictive models for risk insights

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You should have experience with data visualization tools (Tableau, PowerBI, matplotlib, etc.), with strong ability to communicate complex findings effectively

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Knowledge of Machine Learning/Artificial Intelligence, Expertise in Coding, Supervised and Unsupervised Techniques is preferred but not mandatory

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knowing generative ai and machine learning opens doors to roles in automation, mlops, and ai engineering. understanding concepts like rag and vector search improves your ability to build smart solutions

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You have to develop and maintain dashboards, reports and visualizations to communicate key findings and insights to stakeholders to enable data-driven decision-making.

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platforms like azure ml, aws sagemaker, and google vertex ai simplify model deployment, basic exposure to these cloud tools helps you understand how enterprise ai systems work

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Excellent problem-solving, communication, and project management skills; including the ability to handle multiple tasks simultaneously in a fast-paced environment is crucial 

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Hope you read and understand the all criteria carefully , if yes then check below and apply now & share with your friends so they will get benefits 

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