American Express is hiring for the role of Analyst – Data Science in Gurugram, Haryana with a hybrid working model. This opportunity is suitable for candidates with 0–4 years of experience in analytics, data science, or big data roles.
In this role, you will work with the Model Risk Management Group (MRMG), which is responsible for overseeing and managing risks related to enterprise-wide analytical and AI models used across the company.
Candidates with strong skills in machine learning, statistics, analytics, and programming tools such as Python, R, SQL, or SAS will be well-suited for this position.
About the Company
American Express is one of the world’s leading financial services companies, known for its credit cards, payment systems, and financial technology innovations. Founded more than 175 years ago, the company serves millions of customers globally and is recognized for its focus on innovation, customer trust, and employee growth.
The organization invests heavily in data science, artificial intelligence, and risk analytics to enhance decision-making in areas such as fraud detection, credit risk assessment, and customer experience optimization.
Role Overview
The Analyst – Data Science role focuses on managing and controlling risks associated with Artificial Intelligence (AI) and Machine Learning (ML) models used across the enterprise.
The selected candidate will work on model validation, risk assessment, and research related to AI/ML models used in areas like marketing analytics, fraud detection, and credit risk.
This role also involves collaborating with cross-functional teams to ensure that models meet regulatory standards and enterprise risk management frameworks.
Responsibilities
Key responsibilities for this role include:
• Conducting independent oversight of enterprise-wide analytical models, especially AI and ML models
• Evaluating models used in marketing, credit risk, fraud detection, and business analytics
• Performing gap assessments to strengthen model risk control frameworks
• Conducting AI/ML research to support innovation and regulatory compliance
• Communicating analytical insights and validation outcomes to senior leadership and model committees
• Collaborating with cross-functional teams to improve model governance and performance
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Experience Required
| Requirement | Details |
|---|---|
| Experience | 0–4 Years |
| Domain | Analytics, Data Science, or Big Data |
| Work Model | Hybrid |
| Location | Gurugram, Haryana, India |
This role is suitable for entry-level analysts or early-career data science professionals.
Educational Qualifications
Applicants should have one of the following qualifications:
• MBA from a reputed institute
• Master’s degree in Statistics, Economics, Data Science, or related fields
• Equivalent postgraduate qualification in a quantitative discipline
Technical Skills Required
Candidates should have experience with at least one of the following tools:
• Python
• R
• SQL
• SAS
Other important technical skills include:
• Advanced statistical and quantitative analysis techniques
• Machine learning model development or validation
• Data manipulation and analytics workflows
Functional Skills
Successful candidates should also possess:
• Strong analytical and problem-solving abilities
• Good project management and collaboration skills
• Ability to communicate complex analytical insights to business stakeholders and leadership teams
• Adaptability to work in fast-paced and evolving environments
Salary (Market Estimate)
For the Analyst – Data Science role at American Express, the estimated salary range based on industry benchmarks and similar roles is:
| Experience Level | Estimated Salary |
|---|---|
| 0 – 1 Years | ₹10 LPA – ₹14 LPA |
| 2 – 4 Years | ₹14 LPA – ₹20 LPA |
Actual compensation may vary depending on experience, educational background, interview performance, and internal company policies.
In addition to base salary, American Express typically offers performance bonuses, benefits packages, and career development programs.
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Benefits and Perks
Employees at American Express receive several benefits, including:
• Competitive salary and bonus incentives
• Medical, dental, vision, and life insurance benefits
• Retirement and financial well-being programs
• Hybrid work flexibility
• Paid parental leave policies
• Access to wellness programs and counseling support
• Career development and training opportunities
How to Apply
Interested candidates can apply by clicking the Apply button below. Before applying, ensure your resume highlights your experience with data science tools such as Python, SQL, R, or SAS, along with your knowledge of machine learning and statistical modeling.
If you have worked on data science projects, predictive models, or analytics dashboards, include those in your resume. Adding links to GitHub repositories, research projects, Kaggle profiles, or portfolio work can significantly strengthen your application.
You should also highlight your ability to translate analytical findings into business insights, as this is an important skill for data science roles in large organizations.
Disclaimer
This job information is collected from official and publicly available sources. We do not charge any fees for job applications, do not guarantee recruitment, and do not take responsibility for any losses arising from reliance on this information.
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