American Express – Analyst (Data Science)

Job Description

The Analyst – Data Science role at American Express is a high-impact opportunity to work at the heart of data-driven decision-making within the Credit & Fraud Risk (CFR) organization. This role focuses on using advanced analytics, machine learning, and statistical modeling to guide critical business decisions that affect millions of customers globally. As part of the CFR Analytics & Data Science Center of Excellence, you will help American Express grow profitably while maintaining industry-leading standards in credit risk management and fraud prevention.

In this role, you will contribute to the development, deployment, and validation of predictive models that influence decisions across risk, fraud, underwriting, and marketing. You will work with large-scale datasets derived from Amex’s closed-loop network, enabling deeper insights into customer behavior and transaction patterns. By applying economic logic and advanced modeling techniques, you will help ensure decisions are intelligent, scalable, and aligned with delivering a world-class customer experience.

This position offers exposure to one of the most respected analytics environments in the financial services industry. You will collaborate with global stakeholders, senior leaders, and cross-functional teams while solving complex, real-world problems. Ideal for early-career professionals passionate about data science, this role provides strong learning opportunities, access to cutting-edge tools, and the chance to make a measurable impact in a fast-paced, innovation-driven organization.

Roles & Responsibilities

• Develop, deploy, and validate predictive models that support decision-making across credit risk, fraud prevention, and marketing domains.

• Analyze large and complex datasets to uncover insights, patterns, and opportunities that drive profitable business growth.

• Apply supervised and unsupervised machine learning techniques to improve risk assessment and customer targeting strategies.

• Leverage American Express’s closed-loop data ecosystem to create intelligent, relevant, and scalable analytics solutions.

• Translate analytical findings into clear, structured business insights for leadership and key stakeholders.

• Collaborate closely with cross-functional partners across global teams to deliver analytics-driven outcomes.

• Innovate continuously by exploring new modeling approaches, big data techniques, and emerging trends in analytics and payments.

• Ensure models align with economic logic, regulatory standards, and long-term risk management objectives.

• Maintain awareness of external developments in finance, payments, analytics, and data science to inform solution design.

Requirements & Eligibility

• MBA or Master’s degree in Economics, Statistics, Computer Science, or a related quantitative field.

• 0–30 months of hands-on experience in analytics, data science, or big data workstreams.

• Strong programming and analytical skills using tools such as SAS, R, Python, SQL, Hive, Spark, or similar technologies.

• Solid understanding of machine learning techniques including decision trees, neural networks, Bayesian models, reinforcement learning, and graphical models.

• Experience with feature engineering, model evaluation, and large-scale data processing frameworks such as MapReduce.

• Ability to manage project deliverables independently and drive results in complex, unstructured problem spaces.

• Strong problem-solving mindset with the ability to learn quickly and adapt to evolving business needs.

• Excellent communication and interpersonal skills to work effectively with global, cross-functional teams.

• Interest in finance, payments, risk management, and analytics-driven business decisioning.

Expected Salary

For the Analyst – Data Science role at American Express in Gurugram or Bengaluru, the expected salary typically ranges between ₹12 LPA to ₹20 LPA, depending on educational background, technical expertise, and prior experience. In addition to base pay, employees may receive performance-based bonuses and a comprehensive benefits package supporting financial, physical, and mental well-being.

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