Are you looking to build a career in data science, analytics, machine learning, and risk management? The Data Science Analyst opportunity at American Express is a strong option for candidates who want to work on real-world business problems involving fraud detection, credit risk, customer analytics, and predictive modeling.
The Data Science Analyst role is part of the Credit and Fraud Risk Analytics & Data Science team. The position involves working with large datasets, developing analytical solutions, applying machine learning techniques, and turning complex data into useful business insights.
If you have a background in statistics, economics, computer science, analytics, or a related field and are interested in Python, SAS, R, SQL, Spark, Hive, and machine learning, this opportunity is worth exploring.
- 1 Data Science Analyst Recruitment 2026 – Overview
- 2 About American Express
- 3 About the Data Science Analyst Role
- 4 Data Science Analyst Eligibility Criteria
- 5 Data Science Analyst – Skills at a Glance
- 6 Work Location
- 7 Career Growth After Data Science Analyst
- 8 Why Consider This Data Science Analyst Opportunity?
- 9 Important Application Details
- 10 Final Thoughts
Data Science Analyst Recruitment 2026 – Overview
| Job Details | Information |
|---|---|
| Company | American Express |
| Job Role | Data Science Analyst |
| Job Category | Data Management & Analytics |
| Job Location | Gurugram, Haryana & Bengaluru, Karnataka |
| Work Mode | Hybrid |
| Experience | 0–30 months |
| Employment Type | Full-Time |
| Career Area | Analytics & Risk Management |
| Education | MBA / Master’s in relevant field |
| Key Skills | Python, SAS, R, SQL, Hive, Spark, Machine Learning |
| Job ID | 26012381 |
About American Express
American Express is a global financial services company known for its payment products, financial solutions, and customer-focused services. The company uses technology, analytics, and data science extensively to make better decisions and improve customer experiences.
For a Data Science Analyst, this creates an opportunity to work with large-scale datasets and solve problems that can directly influence business decisions.
The Credit and Fraud Risk team focuses on reducing fraud and credit losses while helping the company maintain a strong customer experience. Data science plays an important role in making these decisions more accurate and efficient.
About the Data Science Analyst Role
The Data Science Analyst position focuses on using data, statistics, predictive modeling, and machine learning to support business decisions across areas such as credit risk, fraud, and marketing.
The selected candidate will analyze large volumes of data, identify patterns, develop innovative analytical solutions, and communicate findings to business leaders and cross-functional teams.
This is particularly suitable for candidates who enjoy combining technical data skills with business problem-solving.
Data Science Analyst Eligibility Criteria
Candidates applying for the Data Science Analyst position should meet the educational and experience requirements mentioned in the job description.
Educational Qualification
Preferred educational backgrounds include:
- MBA
- Master’s degree in Economics
- Master’s degree in Statistics
- Master’s degree in Computer Science
- Related analytical or quantitative fields
Experience
The listed experience requirement is 0–30 months in analytics or big-data-related workstreams.
This makes the position relevant to candidates at an early stage of their analytics career.
Data Science Analyst – Skills at a Glance
Work Location
The Data Science Analyst position is available in:
| Location | Work Mode |
|---|---|
| Gurugram, Haryana | Hybrid |
| Bengaluru, Karnataka | Hybrid |
The position is listed as a full-time role with a day shift.
Career Growth After Data Science Analyst
The Data Science Analyst role can provide a strong foundation for a long-term career in analytics and data science.
With experience, professionals can move toward roles such as:
- Senior Data Analyst
- Data Scientist
- Machine Learning Engineer
- Risk Analyst
- Fraud Analytics Specialist
- Business Analyst
- Analytics Consultant
- Senior Data Scientist
- Risk Modeler
- Data Science Manager
The exact career path will depend on individual performance, technical specialization, and experience.
Why Consider This Data Science Analyst Opportunity?
The position provides exposure to several areas of modern analytics, including data science, machine learning, big data, risk analytics, and fraud detection.
You can also gain experience working on business problems that affect a large customer base while collaborating with experienced analytics professionals.
For candidates interested in financial services and data science, this combination can make the Data Science Analyst position a valuable early-career opportunity.
Important Application Details
The job listing provides the following information:
| Information | Details |
|---|---|
| Job Identification | 26012381 |
| Job Role | Data Science Analyst |
| Company | American Express |
| Posted Date | August 10, 2026 |
| Apply Before | August 19, 2026 |
| Experience | 0–30 months |
| Job Type | Full-Time |
| Shift | Day |
| Work Mode | Hybrid |
Candidates should check the official job listing for the latest application status and requirements before applying.
Final Thoughts
The Data Science Analyst opportunity at American Express is a promising option for candidates interested in combining data analytics, machine learning, programming, and business problem-solving.
With opportunities to work on credit risk, fraud prevention, predictive modeling, and large-scale analytics, the role can provide valuable exposure to real-world data science applications.
If you have a relevant master’s or MBA background, up to 30 months of analytics experience, and skills in Python, SQL, SAS, R, Spark, Hive, and machine learning, the Data Science Analyst position could be a strong opportunity to take the next step in your analytics career.
