American Express is Hiring Analyst – Data Science
Credit & Fraud Risk (CFR) | Gurugram & Bengaluru
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Job Overview
American Express is hiring an Analyst – Data Science for its Credit & Fraud Risk (CFR) Analytics & Data Science team in Gurugram and Bengaluru. The role focuses on developing, deploying, and validating predictive models that support profitable business decisions across credit risk, fraud, and marketing.
The selected candidate will analyze large datasets, develop machine learning solutions, generate business insights, and communicate analytical findings to leadership and business partners.
💡 Why this role?
This opportunity is suitable for candidates with 0–30 months of experience and a strong academic background in Economics, Statistics, or Computer Science, wanting to leverage Data Science to solve real-world financial challenges within a global enterprise.
This opportunity is ideal for candidates searching for:
Key Responsibilities
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Understand the core business of American Express and the key factors influencing business decisions.
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Analyze large datasets to identify meaningful business insights and develop innovative analytical solutions.
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Develop, deploy, and validate predictive models, supporting their use within economic decision logic.
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Apply analytics and data science to credit risk, fraud, and marketing decisions using Big Data and ML techniques.
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Structure and communicate business findings to leadership and collaborate with cross-functional partners worldwide.
Eligibility Criteria
Core Competence Required
Candidates must hold an MBA or Master’s degree in Economics, Statistics, Computer Science, or a related field. Must possess 0–30 months of experience in analytics or big data workstreams.
*Preferred Qualifications: Expertise in coding, strong algorithm development knowledge, and high-performance computing experience.*
How to Apply
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Complete Registration
Review the eligibility requirements and submit your updated resume before 19 August 2026.
⚠️ Openings fill quickly. We recommend applying as soon as possible.