Analyst-Data Analytics (SQL, Python, GenAI)

The American Express interview process typically starts with a timed online assessment focusing on quantitative aptitude, logical reasoning, and basic coding in Python/SQL. Successful candidates move to a technical interview where they solve case‑study problems, discuss statistical modeling approaches, and demonstrate data‑visualisation skills. The final HR round assesses cultural fit, communication, and motivation. Overall difficulty is moderate to high; thorough preparation on analytics fundamentals and clear articulation of past projects are key.

American Express promotes a collaborative, inclusive culture where employees are encouraged to innovate and take ownership. The company offers structured career progression, regular learning workshops, and a healthy work‑life balance through flexible hybrid arrangements. Employees benefit from robust wellness programs and global exposure.

Bachelor's degree in a quantitative discipline (B.Tech, B.Sc/M.Sc Statistics, Economics or related). Minimum 60% aggregate or CGPA 6.5/10. No active backlogs; maximum one backlog allowed at the time of joining. Fresh graduates from the 2026 batch are preferred. Strong analytical aptitude and communication skills are mandatory.

Round 1: Online Assessment (aptitude + coding) → Round 2: Technical Interview (SQL, Python, statistics, case studies) → Round 3: HR Interview (fit, culture, expectations)

American Express, a global leader in payment solutions and financial services, has been operating in India for over two decades. The company is known for its strong culture of innovation, customer centricity, and a commitment to employee growth. With a presence across major Indian metros, Amex offers a dynamic work environment where fresh talent can contribute to world‑class products while learning from seasoned professionals. The firm’s emphasis on diversity, inclusion, and community impact makes it an attractive destination for ambitious graduates. The Analyst‑Data Analytics role sits within the AIM (Analytics, Investment & Marketing Enablement) team of Global Commercial Services (GCS) Marketing. As a Band‑30 analyst, you will be the analytical engine that powers acquisition campaign measurement across multiple channels and product lines. Your day‑to‑day responsibilities will involve translating raw data from Hive, SQL, and PySpark into actionable insights that drive marketing strategy, improve ROI, and support senior leadership decision‑making. You will work closely with marketing stakeholders, business partners, and functional leaders, delivering monthly performance reports, building visual case studies, and piloting new analytical solutions in a fast‑paced, ambiguous environment. Key responsibilities include: 1. Supporting business partners with campaign measurement, ROI analysis, and data‑driven recommendations. 2. Gathering requirements, performing deep‑dive data analysis, and presenting findings to GCS teams. 3. Delivering accurate, timely monthly results reporting for marketing and sales leadership. 4. Exploring and visualising data from diverse sources using Tableau/Power BI. 5. Quickly learning new business domains and driving pilot projects under uncertainty. 6. Collaborating with functional leaders to assess feasibility, ensure data integrity, and provide actionable insights. 7. Building strong partnerships with marketing stakeholders and owning end‑to‑end project delivery. 8. Demonstrating ownership, growth mindset, and the ability to work with flexible shift timings for global partners. The tech stack revolves around Hive, Python, PySpark, SQL, Tableau, Power BI, and advanced Excel. A solid foundation in statistical techniques—hypothesis testing, regression, KNN, t‑test, chi‑square—is essential. The role offers a clear growth trajectory: Analyst → Senior Analyst → Analytics Manager → Director of Marketing Analytics, with ample opportunities for upskilling in GenAI, machine learning, and leadership. Why join American Express? You will be part of a globally recognised brand that invests heavily in employee well‑being, offering competitive salaries, bonus incentives, comprehensive health benefits, flexible hybrid work, and robust learning programs. The culture encourages curiosity, collaboration, and continuous improvement, making it an ideal launchpad for a data‑analytics career.