If you are an early-career professional with a background in data science, statistics, economics, computer science or analytics, the American Express Off Campus Hiring opportunity for the Analyst – Data Science role could be an interesting career option to explore.
American Express is hiring for an Analyst – Data Science position within its Credit and Fraud Risk (CFR) Analytics & Data Science Center of Excellence. The role focuses on predictive modeling, machine learning, big data, fraud and credit risk analytics, and business decision-making.
The position is available in Gurugram and Bengaluru, with a hybrid work model. Candidates with 0–30 months of experience can be considered, making this an early-career opportunity for recent graduates and professionals with limited industry experience.
American Express Off Campus Hiring – Job Overview
| Job Details | Information |
|---|---|
| Company | American Express |
| Job Role | Analyst – Data Science |
| Focus Keyword | American Express Off Campus Hiring |
| Job Category | Data Management and Analytics |
| Career Area | Analytics & Risk Management |
| Job ID | 26012381 |
| Locations | Gurugram, Haryana & Bengaluru, Karnataka |
| Work Model | Hybrid |
| Employment Type | Full Time |
| Experience | 0–30 Months |
| Education | MBA / Master’s in Economics, Statistics, Computer Science or related field |
| Key Technologies | SAS, R, Python, Hive, Spark, SQL |
| Core Areas | Data Science, Machine Learning, Risk & Fraud Analytics |
| Posting Date | 17 September 2026 |
| Apply Before | 21 September 2026 |
| Job Shift | Day |
| Salary | Not specifically disclosed in the supplied job description |
About the American Express Off Campus Hiring Opportunity
The American Express Off Campus Hiring opportunity is part of the company’s Credit and Fraud Risk (CFR) Analytics & Data Science team.
The team uses data science, analytics and technology to help American Express make better decisions around credit, fraud, customers and financial risk.
A decision made by a financial services company can affect millions of customers. Because of this, predictive analytics and machine learning play an important role in determining how businesses assess risk while continuing to provide a smooth customer experience.
As an Analyst – Data Science, candidates will contribute to this data-driven environment by developing, deploying and validating predictive models.
What Does an Analyst – Data Science Do?
The main objective of the role is to develop and support predictive models that can help American Express make profitable decisions across areas such as:
- Credit risk
- Fraud risk
- Marketing
- Customer management
- Financial services
- Risk decisioning
The position combines technical data science knowledge with business understanding.
This means candidates need more than programming skills. They should also be able to understand a business problem, analyze data, develop an appropriate analytical approach and explain the resulting insights to stakeholders.
Key Responsibilities in American Express Off Campus Hiring
1. Understand the Business
One of the first responsibilities is understanding the core business of American Express and the factors that influence different business decisions.
A strong data scientist needs to understand why a model is being built, not simply how to build it.
Candidates should therefore develop an understanding of:
- Financial services
- Credit risk
- Fraud
- Payments
- Customer behavior
- Business decision-making
Qualifications for American Express Off Campus Hiring
The supplied job description lists the following educational backgrounds:
- MBA
- Master’s degree in Economics
- Master’s degree in Statistics
- Master’s degree in Computer Science
- Related fields
The experience requirement is:
0–30 months of experience in analytics or big data workstreams.
This makes the position relevant to recent graduates and early-career professionals, although it is not described as a fresher-only role.
Is American Express Off Campus Hiring for Freshers?
The role can be relevant to freshers and recent graduates because the listed experience range starts at 0 months.
However, the qualification section specifically asks for an MBA or master’s degree in Economics, Statistics, Computer Science or a related field.
Therefore, candidates should carefully check whether their educational background matches the current requirements before applying.
The opportunity is better described as an early-career data science position rather than a role exclusively for freshers.
Important Machine Learning Topics to Prepare
Candidates preparing for the American Express Off Campus Hiring opportunity should revise:
Supervised Learning
- Regression
- Classification
- Decision trees
- Model evaluation
- Feature engineering
Unsupervised Learning
- Clustering
- Dimensionality reduction
- Pattern discovery
Advanced Concepts
- Neural networks
- Reinforcement learning
- Transfer learning
- Bayesian models
- Graphical models
- Gaussian processes
The level of preparation should be aligned with your academic and professional experience.
Skills Beyond Data Science
American Express is also looking for strong professional skills.
Problem Solving
Candidates should be able to approach complex and unstructured problems logically.
Communication
The role requires explaining analytical findings to leadership and business partners.
Collaboration
Data science projects often involve working with teams across different functions and locations.
Independent Learning
The job description highlights the ability to learn quickly and work independently.
Business Understanding
Candidates should understand how analytics can be connected to business outcomes rather than treating machine learning as an isolated technical exercise.
Career Growth After Analyst – Data Science
An early-career position in data science and risk analytics can provide experience across several technical and business areas.
Depending on experience, skills and future opportunities, possible career paths can include:
- Data Analyst
- Data Scientist
- Risk Analyst
- Fraud Analytics Specialist
- Machine Learning Engineer
- Senior Data Scientist
- Risk Modeler
- Analytics Consultant
- Quantitative Analyst
Building strong foundations in Python, SQL, statistics, machine learning and business analytics can help candidates develop their careers in data-driven roles.
What American Express Offers
The supplied job description mentions several employee benefits and development opportunities, including:
- Competitive base salary
- Bonus incentives
- Financial well-being and retirement support
- Medical, dental and vision benefits depending on location
- Life insurance and disability benefits depending on location
- Flexible working arrangements
- Paid parental leave depending on location
- Wellness support
- Counseling through the Healthy Minds programme
- Career development
- Training and learning opportunities
Benefits can vary depending on location and applicable employment terms.
Final Words
The American Express Off Campus Hiring opportunity for Analyst – Data Science is aimed at early-career professionals interested in combining data science, machine learning and financial risk analytics.
With exposure to credit and fraud risk problems, predictive modeling, big data and business decision-making, the role can provide practical experience in a highly data-driven financial services environment.
Candidates should focus their preparation on Python, SQL, statistics, machine learning, predictive modeling and business communication. It is equally important to understand how analytical models can solve real business problems rather than focusing only on technical implementation.
If your education and experience match the requirements, review the official job details carefully and apply before the stated deadline.
