Global financial services leader American Express (Amex) is hiring for the position of Analyst – Data Science under Job Identification: 26012381. Hosted on an enterprise Oracle Cloud HCM portal (egug.fa.us2.oraclecloud.com), this role is situated within American Express’s Credit and Fraud Risk (CFR) Analytics & Data Science CoE team.
This position focuses on applying predictive modeling, advanced machine learning, and big data engineering to optimize credit decisioning, mitigate fraud risk, and power customer underwriting across global Amex networks.
Job Details
| Attribute | Information |
| Role Title | Analyst – Data Science |
| Job Identification Number | 26012381 |
| Company Entity | American Express (Amex) |
| Business Unit / Division | Credit & Fraud Risk (CFR) / Data Mgmt & Analytics |
| Work Locations | Gurugram, HR & Bengaluru, KA, India (Hybrid Work Model) |
| Employment Type | Full-Time, Permanent |
| Experience Required | 0 to 30 Months (0 to 2.5 Years) |
| Posting Date | September 16, 2026 |
| Application Deadline | September 20, 2026 (11:30 AM) |
About Company
American Express is a globally integrated payments company headquartered in New York, providing customers with access to products, insights, and experiences that enrich lives and build business success.
The Credit and Fraud Risk (CFR) group serves as the analytical backbone of American Express. The CFR Analytics & Data Science Center of Excellence (CoE) drives profitable business growth by maintaining the industry’s lowest credit loss and fraud rates.By analyzing millions of daily transactions, the team ensures smart underwriting, fraud prevention, and personalized customer experiences powered by closed-loop data networks.
Comprehensive Job Overview
As an Analyst – Data Science, you will tackle real-world financial risk and machine learning challenges.You will design, build, test, and deploy predictive models and data pipelines that guide decisions across customer targeting, credit underwriting, fraud detection, and post-onboarding account management.
In this role, you will work with massive unstructured datasets using modern big data infrastructure and advance traditional machine learning frameworks through active learning, neural architectures, and attribute engineering.
Requirements & Qualifications
1. Educational Background
- Degree:Master’s Degree (MBA, M.Tech, M.S., or M.Sc.) in Economics, Statistics, Computer Science, Data Science, Quantitative Finance, or related analytical fields.
2. Core Experience
- 0 to 30 Months (0 to 2.5 Years)of relevant hands-on experience in analytics, data science, machine learning, or big data workstreams.
3. Core Technical Skills
- Programming Languages:Hands-on proficiency in Python, SQL, SAS, and R.
- Big Data Frameworks: Practical experience using PySpark / Spark, Hive, and MapReduce architectures to analyze enterprise-scale datasets.
- Machine Learning & Modeling: Proven knowledge of supervised and unsupervised techniques, including:
- Decision Trees, Random Forests, & Gradient Boosting
- Neural Networks & Deep Learning Models
- Active Learning, Transfer Learning, & Reinforcement Learning
- Gaussian Processes, Bayesian Models, & Graphical Models
- Attribute Engineering & Feature Selection
4. Preferred / Soft Skills
- Strong problem-solving mindset with the ability to structure complex, unstructured business problems.
- High communication ability to translate technical model outputs into actionable business recommendations for executive leadership.
- Capability to integrate effectively with global cross-functional partners.
Telegram Channel:Click Here to Join
Key Roles and Responsibilities
- Predictive Model Development:Build, validate, and deploy risk models and algorithmic logic to power financial decisions across credit, fraud, and marketing.
- Big Data Analytics:Analyze high-volume transaction datasets using closed-loop Amex data to extract business insights and create data products.
- Machine Learning Innovation: Research and introduce advanced algorithmic techniques (attribute engineering, reinforcement learning, transfer learning) to optimize decision accuracy.
- Business Insight Articulation:Synthesize analytical findings into strategic narratives and present clear recommendations to cross-functional leads.
- Cross-Functional Integration: Partner closely with global product owners, risk managers, and engineering teams to integrate algorithms into live decisioning engines.
WhatsApp Group:Click Here to Join
Technical Tools & Domain Summary
| Domain | Technologies & Methods |
| Programming Languages | Python, SQL, R, SAS |
| Big Data Ecosystem | Apache Spark, PySpark, Hive, MapReduce |
| Machine Learning | Decision Trees, Neural Networks, Active Learning, Transfer Learning, Reinforcement Learning |
| Statistical Methods | Bayesian Modeling, Gaussian Processes, Attribute Engineering, Graphical Models |
| Business Applications | Credit Risk Underwriting, Fraud Mitigation, Customer Targeting, Risk Analytics |
How to Apply?
- Open the official American Express Oracle Cloud HCM link provided below.
- Sign in or create a candidate account.
- Verify Job Identification: 26012381 for Gurugram or Bengaluru, India.
- Fill in your personal details, upload a tailored resume highlighting Python, SQL, Spark, and Machine Learning experience, and complete the application.
Official Application Link:Apply Link
Compensation & Benefits
- Salary & Bonus:Competitive industry base salary accompanied by performance-based annual bonus incentives.
- Work Model:Flexible hybrid working policy (mix of remote and in-office).
- Healthcare & Wellness:Comprehensive medical, dental, vision, life, and disability coverage.On-site wellness centers staffed with healthcare professionals.
- Mental Health Backing:Free, confidential counseling and emotional wellness programs through the Healthy Minds platform.
- Leave & Time Off:Generous paid parental leave policies along with personal time off.
Selection & Recruitment Process
- Profile Shortlisting: Screening based on educational background (Master’s/MBA), Python/SQL proficiency, and risk analytics/ML skills.
- Technical Online Assessment: Coding and analytical evaluation covering SQL data manipulations, Python data science libraries, probability/statistics, and machine learning concepts.
- Technical Interview Round 1 (Data Science & SQL): Deep dive into machine learning algorithms, attribute engineering, feature selection, and complex SQL query formulation.
- Technical Interview Round 2 (Case Study & Risk Analytics): Practical business case study assessing how you apply machine learning to solve fraud detection, risk scoring, or customer underwriting scenarios.
- Managerial & Culture Fit Round:Discussion on leadership behaviors, handling unstructured problems, cross-functional collaboration, and alignment with American Express core values.