American Express is hiring an Analyst-Data Science for its Model Risk Management Group in Gurugram, Haryana. The role is suited to candidates with a Master’s degree or MBA in a quantitative field and 0–2 years of relevant experience. The analyst will assess and monitor Generative AI, LLM and machine-learning models used across areas such as marketing, credit, fraud, customer engagement and risk decisioning. It is worth considering for early-career professionals who want hands-on exposure to responsible AI, model governance and enterprise risk management within a global financial services organisation.
Company Overview
American Express is a global financial services company known for its payment products, customer service and risk-focused operations. With a 175-year history of innovation and a large enterprise operating across multiple business areas, the company offers experience in analytics, financial services, compliance and technology that can add strong value to an early-career professional’s CV.
| Company Name | American Express |
| Job Role | Analyst-Data Science |
| Qualification | MBA or Master’s Degree in Statistics, Economics, Data Science, AI/ML, Generative AI or related quantitative fields from a top-tier institute |
| Job Location | Gurgaon |
| Employment Type | Full Time |
| Experience | 0–2 years |
| Category | Latest Freshers Jobs |
Role Overview
The Analyst, Data Science role sits within the Model Risk Management Group under American Express’ Global Risk and Compliance organisation. The position supports independent oversight of AI and machine-learning models, with a focus on making model use more robust, explainable and aligned with internal controls and regulatory expectations.
- Review Generative AI, LLM-based and advanced machine-learning models used across the enterprise.
- Examine model design, training data, prompt approaches, assumptions, performance and monitoring controls.
- Study risks involving bias, explainability, robustness and misuse in AI systems.
- Prepare analytical findings and risk-focused insights for business and risk stakeholders.
Eligibility & Qualifications
- Applicants must hold an MBA or Master’s degree in Statistics, Economics, Data Science, AI/ML, Generative AI or a related quantitative field.
- The qualification should be from a top-tier institute.
- Candidates with 0–2 years of experience in analytics, data science, model development, validation or big-data workstreams can apply.
- Exposure to AI/ML model development, testing or validation through professional experience, projects or internships is preferred.
- Early exposure to or interest in Generative AI and LLM-based systems is a strong advantage.
- Employment is subject to successful completion of a background verification check, as applicable under relevant laws and regulations.
Key Responsibilities
- Support independent oversight and effective challenge of Generative AI, LLM-based and advanced ML models.
- Participate in risk-based GenAI model reviews covering objectives, architecture, training data, prompt design and assumptions.
- Execute model risk testing, documentation reviews and evidence assessments in line with Model Risk Management Group standards.
- Conduct gap assessments against internal policies and external regulatory expectations for AI and ML models.
- Research developments in AI/ML, Generative AI, AI risk management and regulatory requirements.
- Prepare structured analysis, validation notes and risk summaries for internal stakeholders.
- Communicate findings to business partners, model committees and senior leaders with guidance from managers.
- Work with data science, engineering, product and risk teams to support validation activities.
- Help build consistent, scalable and defensible GenAI risk management practices across the enterprise.
- Improve the efficiency and quality of MRMG processes through disciplined analysis and documentation.
Skills Required
- Foundational understanding of AI and machine-learning concepts.
- Interest in Generative AI technologies and LLM-based systems.
- Hands-on experience with at least one of Python, PySpark, R or SQL.
- Ability to work with data, perform analytical checks and support model evaluation.
- Strong analytical, problem-solving and structured-thinking skills.
- Clear written and verbal communication skills.
- Ability to explain analytical results to diverse audiences.
- Ability to manage multiple tasks, adapt to changing priorities and meet tight timelines.
- Curiosity, learning agility and willingness to challenge assumptions responsibly.
- Integrity in analysis, collaboration skills and an enterprise-oriented approach to work.
Why Join American Express
Team Amex provides opportunities to learn new skills, develop as a leader and grow through career development and training programmes. The role also offers exposure to enterprise-wide AI governance, model risk controls and collaboration with data science, engineering, product and risk teams. American Express supports employee well-being through benefits covering physical, financial and mental health, along with flexible working models depending on business requirements.
How to Apply for American Express Hiring 2026
Eligible and Interested candidates can apply using the below-mentioned link before the link expires. Applicants need to register with the company portal in order to complete the registration process.
Apply Link: Click Here To Apply
