Associate Data Analyst

The American Express interview process typically starts with an online aptitude and coding test, followed by a technical interview focusing on machine‑learning concepts, Python coding, and case‑study discussions. A final HR round assesses cultural fit, communication skills, and motivation. The difficulty is moderate to high, with an emphasis on problem‑solving ability and clear articulation of analytical findings. Preparing with real‑world AI risk scenarios and strong fundamentals in statistics helps candidates stand out.

American Express promotes a collaborative, inclusive environment where learning and innovation are encouraged. Employees enjoy flexible hybrid work options, robust wellness programs, and clear career progression pathways. The company places a strong emphasis on work‑life balance and supports continuous upskilling through internal training platforms.

MBA or Master's degree in Statistics, Economics, Data Science, AI/ML, Generative AI or related quantitative fields from a top‑tier institute; 0–2 years of experience in analytics, data science, model development or validation; minimum 60% aggregate (or CGPA 6.5/10) in the qualifying degree; no active backlogs at the time of joining; eligible batch 2025‑2027 (preferably 2026).

Round 1: Online Assessment (aptitude & basic coding) → Round 2: Technical Interview (ML concepts, Python, case studies) → Round 3: HR Interview (fit & culture) → Final Offer

American Express, a global leader in payment and travel solutions, has a 175‑year legacy of innovation, customer focus, and risk‑aware culture. Headquartered in New York, the company operates in more than 130 countries, offering a wide range of financial products and services. In India, Amex has built a strong presence with a focus on technology‑driven products, a collaborative work environment, and a commitment to diversity and inclusion. Employees benefit from extensive learning programs, wellness initiatives, and a clear path for career growth. The Analyst‑Data Science role sits within the Model Risk Management Group (MRMG) of the Global Risk and Compliance organization. The team is responsible for independent oversight of Generative AI, large language models (LLMs), and advanced machine‑learning applications that power critical business functions such as marketing, credit underwriting, fraud detection, and customer engagement. As a fresh graduate or early‑career professional, you will work closely with senior risk analysts, data scientists, and product owners to evaluate model design, data quality, performance metrics, and governance controls. Your insights will help the enterprise deploy AI responsibly while meeting evolving regulatory expectations. Key responsibilities include: 1. Supporting independent risk reviews of GenAI and ML models across the enterprise. 2. Assessing model objectives, architecture, training data, prompt design, and underlying assumptions. 3. Evaluating model performance, monitoring frameworks, and control mechanisms. 4. Identifying and documenting risks related to bias, explainability, robustness, and misuse. 5. Executing model risk testing, evidence collection, and documentation in line with MRMG standards. 6. Conducting gap analyses against internal policies and external AI regulations. 7. Researching emerging GenAI trends and translating findings into actionable guidance. 8. Preparing clear risk summaries, validation notes, and presentations for stakeholders. 9. Collaborating with cross‑functional teams—data engineering, product, risk, and compliance—to ensure smooth validation execution. 10. Contributing to the continuous improvement of MRMG processes and risk‑management frameworks. Technical stack: Python (pandas, scikit‑learn, PyTorch), SQL, basic PySpark, statistical analysis, and familiarity with LLM evaluation tools. Strong analytical thinking, structured communication, and the ability to manage multiple priorities are essential. Growth path: Analysts typically progress to Senior Analyst, then to Model Risk Manager, and eventually to leadership roles such as Risk Management Lead or Director of Model Governance. The role provides exposure to cutting‑edge AI technologies and a clear view of enterprise‑wide risk practices, making it an excellent springboard for a career in AI risk, data science, or regulatory compliance. Why join American Express? The company offers a competitive compensation package, robust learning resources, and a culture that values integrity, collaboration, and continuous improvement. Fresh talent gets the chance to work on high‑impact AI projects, receive mentorship from seasoned risk professionals, and contribute to responsible AI deployment at a global scale.