Are you a Post Graduate from a top-tier institute with 0-2 years of experience in Analytics, Data Science, or Machine Learning? Here’s an exceptional opportunity to join American Express as an Analyst-Data Science in Bengaluru or Gurugram! This hybrid role invites you to innovate modeling techniques, incorporate new data intelligence, and conduct AI/ML research to elevate model excellence within the Commercial Collections and Credit Data Science team. If you’re proficient in ML languages, SQL, and possess strong communication skills, seize this chance to make a significant impact and define the future of American Express.
Overview | American Express Recruitment 2025
| Company Name | American Express |
| Job Role | Analyst-Data Science |
| Qualification | Post Graduate Degree |
| Experience | 0-2 Years |
| Salary | INR Upto 15 LPA (Expected) |
| Location | Bengaluru |
Eligibility Criteria | American Express Recruitment 2025
1) Educational Qualifications: A Post Graduate Degree in Statistics, Mathematics, Economics, Engineering, or Management from Top Tier Institutes is required.
2) Graduation Timing: This role is for individuals with 0-2 years of experience, suitable for recent post-graduates or early-career professionals.
3) Work Experience: 0 to 2 years of experience in Analytics, Data Science, Machine Learning, or related fields is the minimum requirement.
4) Technical Skills: Proficiency and experience in econometric, statistical, analytical, and ML techniques are essential. Proficiency in ML languages (Python; PySpark) and SQL/Hive is also mandatory.
5) Soft Skills: Strong communication and interpersonal skills, ability to drive project deliverables, work effectively in a team, and learn quickly with complex, unstructured initiatives are crucial.
Selection Process | American Express Recruitment 2025
1) Application Submission: Submit your application online via the American Express careers portal (ID: 25010834). Ensure your resume highlights your post-graduate degree, relevant experience (0-2 years), and technical proficiencies.
2) Resume Screening: American Express will review applications based on the required post-graduate qualifications, years of experience in relevant fields, and demonstrated technical skills in ML languages and analytical techniques.
3) Technical Test / Interview: Expect a rigorous assessment of your proficiency in econometric, statistical, analytical, and ML techniques. This will likely involve coding tests (Python/PySpark, SQL/Hive) and in-depth technical interviews on data science concepts and model innovation.
4) HR Interview: This round will evaluate your communication and interpersonal skills, ability to work effectively in a team, drive project deliverables, and potential to learn quickly and work independently on complex initiatives.
5) Document Verification & Offer Letter: If successful through all rounds, your academic and personal documents will be verified. Upon successful verification, you will receive an official offer letter for the Analyst-Data Science position.
6) Onboarding Process: Upon accepting the offer, you will go through the onboarding process. This includes completing necessary paperwork and attending orientation to integrate smoothly into the American Express Commercial Data Science & Model Integration team in Bengaluru or Gurugram.
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Roles & Responsibilities | American Express Recruitment 2025
1) Support Data Science Practices: Support Commercial Collections and Credit Data science practices to drive model usage and tackle business opportunities.
2) Innovate Modeling Techniques: Innovate modeling techniques and variable creation to enhance existing models.
3) Incorporate New Data: Integrate new data intelligence from consumer, commercial bureau, and internal datasets into commercial credit risk models.
4) Conduct AI/ML Research: Conduct AI/ML research to explore opportunities that elevate model excellence and drive business impact.
5) Review Customer Cases: Review customer cases to proactively identify new model or variable opportunities.
Skills & Competencies | American Express Recruitment 2025
1) Analytics/Data Science Experience: 0-2 years of experience in Analytics, Data Science, Machine Learning, or related fields.
2) Post Graduate Degree: Required in Statistics, Mathematics, Economics, Engineering, or Management from Top Tier Institutes.
3) ML & Statistical Techniques: Proficiency in econometric, statistical, analytical, and Machine Learning techniques.
4) Programming Proficiency: Strong proficiency in ML languages (Python, PySpark) and database query languages (SQL/Hive).
5) Problem-Solving & Communication: Ability to drive project deliverables, strong communication, interpersonal skills, and quick learning with complex initiatives.
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How to Apply? | American Express Recruitment 2025
- First, read through all of the job details on this page.
- Scroll down and press the Click Here button.
- To be redirected to the official website, click on the apply link.
- Fill in the details with the information provided.
- Before submitting the application, cross-check the information you’ve provided.
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General Interview Questions | American Express Recruitment 2025
General Questions Interview Questions
1) Tell me about yourself and what specifically interests you in a Data Science role at American Express, particularly within Commercial Collections and Credit. How to answer: Introduce your post-graduate background and 0-2 years experience. Express your passion for data science, its application in financial services (credit risk/collections), and your excitement about innovating with AI/ML at Amex.
2) Describe a project where you used Python or PySpark for data analysis or model building. What was the objective, your approach, and the outcome? How to answer: Use the STAR method. Detail the dataset, the specific libraries/functions used, challenges encountered (e.g., data cleaning, feature engineering), and the insights gained or model performance achieved.
3) How do you approach understanding complex, unstructured business problems, and then translating them into a data science problem? How to answer: Discuss active listening, asking clarifying questions, breaking down the problem, identifying key metrics, understanding data availability, and defining clear objectives and success criteria for the data science solution.
4) American Express values teamwork and collaboration. Describe a time you worked effectively in a team environment to deliver a project. How to answer: Focus on your collaborative contributions: how you communicated, shared responsibilities, resolved conflicts, supported teammates, and collectively achieved the project goals.
5) How do you stay updated with the latest advancements in Data Science, Machine Learning, and AI research? How to answer: Mention specific methods like reading research papers (e.g., ArXiv), following reputable blogs/journals, taking online courses, attending webinars, or participating in Kaggle competitions or data science communities.
Role-Specific Interview Questions
1) Explain the difference between supervised and unsupervised learning, and give an example of each relevant to credit risk or collections. How to answer: Define supervised (labeled data, predicts target, e.g., credit default prediction – classification) and unsupervised (unlabeled data, finds patterns, e.g., customer segmentation for collections strategy – clustering).
2) What is overfitting in a machine learning model, and how would you detect and mitigate it? How to answer: Define overfitting as a model performing well on training data but poorly on unseen data. Discuss detection (validation curves, comparing train/test performance) and mitigation techniques (regularization, cross-validation, more data, feature selection, simpler models).
3) You’re asked to incorporate new external data (e.g., commercial bureau data) into an existing credit risk model. What steps would you take from data ingestion to model enhancement? How to answer: Outline steps: data acquisition/validation, data cleaning/pre-processing, feature engineering from new data, exploratory data analysis, feature selection, model retraining/recalibration, performance evaluation, and A/B testing/monitoring.
4) How would you go about evaluating the performance of a commercial credit risk model? What metrics would you use? How to answer: Discuss metrics like AUC-ROC, Gini coefficient, KS statistic, Precision, Recall, F1-score, and Confusion Matrix. Explain why these are relevant for credit risk (balancing false positives/negatives for default prediction).
5) Given the sensitive nature of financial data, what are some key considerations for data privacy, security, and ethical AI in model development for credit risk? How to answer: Discuss data anonymization/pseudonymization, secure data handling, compliance with regulations (e.g., GDPR, CCPA), fairness/bias detection in models, interpretability, and avoiding discriminatory outcomes.
About the Company | American Express Recruitment 2025
American Express is a globally integrated payments company, providing customers with access to products, insights, and experiences that enrich lives and build business success. With a history spanning over 175 years, American Express is built on a strong culture of innovation, shared values, and an unwavering commitment to back its customers, communities, and colleagues. They are a recognized leader in financial services, offering a wide range of credit and charge cards, financial advisory services, and travel-related services to individuals and businesses worldwide.
Conclusion | American Express Recruitment 2025
This Analyst-Data Science position at American Express in Bengaluru or Gurugram presents an outstanding opportunity for Post Graduates from top-tier institutes with 0-2 years of experience. If you are proficient in ML languages, strong in statistical and analytical techniques, and eager to innovate within commercial collections and credit data science, this hybrid role offers a compelling career path.
You’ll be instrumental in developing and enhancing critical credit risk models, incorporating new data intelligence, and conducting cutting-edge AI/ML research. Don’t miss this chance to be part of a purpose-driven organization that values innovation, backs its colleagues, and empowers you to define the future of American Express.
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Frequently Asked Questions | American Express Recruitment 2025
1) What is the required educational qualification for this role?
Ans: A Post Graduate Degree in Statistics, Mathematics, Economics, Engineering, or Management from Top Tier Institutes is required.
2) What is the minimum experience required?
Ans: 0-2 years of experience in Analytics, Data Science, Machine Learning, or related fields.
3) Which programming languages are essential for this position?
Ans: Proficiency in ML languages (Python, PySpark) and SQL/Hive is essential.
4) What are the primary responsibilities in this role?
Ans: Supporting commercial collections/credit data science, innovating modeling techniques, incorporating new data, and conducting AI/ML research.
Disclaimer | American Express Recruitment 2025
The Recruitment Information Provided above is for Informational Purposes only. The above Recruitment Information has been taken from the official site of the Organization. We do not provide any Recruitment guarantee. Recruitment is to be done as per the official recruitment process of the company. We don’t charge any fee for providing this job Information.