American Express Hiring Analyst – Data Science | 0–30 Months Experience | Hybrid | Apply Now

 

Are you passionate about Data Science, Analytics, and Machine Learning? American Express (Amex) is hiring Analysts – Data Science for its Credit & Fraud Risk (CFR) Analytics & Data Science team. This opportunity is ideal for fresh graduates and professionals with up to 30 months of experience who want to work on large-scale data-driven business problems. If you're looking to build a career in analytics while working with one of the world's leading financial services companies, this is an excellent opportunity.

About the Company

American Express (Amex) is one of the world's leading financial services companies, known for its innovation in payments, customer experience, analytics, and digital transformation. With a strong focus on data-driven decision-making, Amex empowers its employees to solve real-world business challenges using advanced analytics, machine learning, and artificial intelligence.

Job Details

Company: American Express

Role: Analyst – Data Science

Job ID: 26007966

Location: Gurugram & Bengaluru

Work Mode: Hybrid

Experience: 0–30 Months

Job Type: Full-Time

Department: Analytics & Risk Management

Application Deadline: 10 July 2026

Eligibility Criteria

• Bachelor's or Master's degree in Computer Science, Statistics, Economics, Mathematics, Data Science, Engineering, or related fields.

• MBA candidates are also eligible.

• 0–30 months of relevant analytics experience.

• Strong analytical and problem-solving skills.

• Excellent communication and teamwork abilities.

Educational Qualification

Candidates should possess a Bachelor's Degree, Master's Degree, or MBA in Computer Science, Statistics, Economics, Mathematics, Data Science, Engineering, or related disciplines from a recognized institution.

About the Team

The Credit & Fraud Risk (CFR) Analytics & Data Science Center of Excellence plays a critical role in helping American Express reduce fraud, improve credit decisions, enhance customer experiences, and enable business growth through advanced analytics, machine learning, and predictive modeling. The team works on projects that impact millions of customers worldwide.

Job Description

As an Analyst – Data Science, you will analyze large datasets, develop predictive models, generate business insights, and collaborate with cross-functional teams to improve decision-making across credit risk, fraud detection, and marketing. You'll work with experienced data scientists and business leaders while solving real-world financial challenges.

Key Responsibilities

• Analyze large datasets to identify business insights.

• Develop and validate predictive models.

• Build machine learning solutions for business problems.

• Support fraud detection and credit risk strategies.

• Collaborate with cross-functional global teams.

• Present analytical findings to business leaders.

• Improve business decisions using advanced analytics.

• Monitor model performance and recommend improvements.

Required Skills

• Data Analytics

• Machine Learning Fundamentals

• Predictive Modeling

• Statistical Analysis

• Business Analytics

• Problem Solving

• Communication Skills

• Team Collaboration

Preferred Skills

• Python

• R Programming

• SQL

• Machine Learning

• Data Visualization

• Big Data Technologies

• Artificial Intelligence

• Risk Analytics

• Financial Analytics

Tools & Technologies

• Python

• R

• SQL

• Machine Learning Libraries

• Data Analytics Tools

• Statistical Modeling

• Business Intelligence Platforms

• Big Data Technologies

Why Join American Express?

• Work with one of the world's leading financial services companies.

• Solve real-world business problems using analytics.

• Exposure to advanced Machine Learning projects.

• Hybrid work model.

• Career growth and leadership development.

• Competitive salary and performance bonuses.

• Comprehensive medical and wellness benefits.

• Paid parental leave.

• Continuous learning and professional development.

• Inclusive and collaborative work environment.

Salary & Benefits

American Express has not officially disclosed the salary for this position.

The compensation package, bonuses, and benefits will depend on the candidate's qualifications, interview performance, experience, and company policies.

Selection Process

Note: American Express has not officially mentioned the recruitment process for this role. The following is the typical hiring process and may vary based on business requirements.

• Online Application

• Resume Screening

• Online Assessment (if applicable)

• Technical/Analytics Interview

• Business Discussion

• HR Interview

• Offer Letter

• Background Verification

Preparation Tips

• Revise Statistics and Probability.

• Practice SQL queries.

• Strengthen Python or R programming.

• Learn Machine Learning fundamentals.

• Practice business case studies.

• Improve communication and presentation skills.

• Work on Data Science projects.

• Prepare for behavioral interview questions.

Who Should Apply?

• Fresh Graduates.

• MBA Graduates.

• Data Science Aspirants.

• Computer Science Graduates.

• Statistics and Mathematics Graduates.

• Economics Graduates.

• Candidates with up to 30 months of analytics experience.

• Individuals passionate about AI, Machine Learning, and Analytics.

How to Apply

Interested candidates should apply through the official American Express Careers portal before the application deadline. Ensure your resume highlights your technical skills, projects, internships, certifications, and relevant academic achievements before submitting your application.

Apply Now

Conclusion

The Analyst – Data Science role at American Express offers an outstanding opportunity to work on large-scale analytics and machine learning projects that impact millions of customers worldwide. If you're passionate about data, predictive analytics, and solving complex business problems, this role provides an excellent platform for long-term career growth in one of the world's most respected organizations.

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Disclaimer

Software Jobs Daily shares job opportunities from official company sources. We are not involved in the hiring process. Candidates are advised to verify all details through the official company website before applying.