Data Analytics

The interview process typically starts with a timed online aptitude test focusing on quantitative, logical, and verbal reasoning. Successful candidates move to a technical interview where they solve SQL/Python case studies and discuss analytics approaches. The final HR round assesses cultural fit, communication skills, and motivation. Overall difficulty is moderate, with emphasis on clear problem‑solving and business‑oriented thinking.

American Express promotes a collaborative and inclusive environment where employees are encouraged to innovate and take ownership of their work. The company offers clear growth pathways, regular upskilling programs, and a balanced hybrid work model that supports both professional development and personal well‑being.

Graduates (B.Tech/B.E., B.Sc., B.Com, MBA) in Computer Science, Information Technology, Statistics, Mathematics, Engineering or related fields; minimum 60% aggregate (or CGPA 6.0/10); batch year 2025 or 2026; no active backlogs; strong analytical mindset and communication skills.

Round 1: Online Aptitude Test → Round 2: Technical Interview (SQL/Python case study) → Round 3: HR Interview

American Express, a global leader in payment services and financial solutions, has a strong presence in India with a focus on innovation, customer centricity, and technology-driven growth. The company’s Indian operations are headquartered in Gurugram and serve millions of merchants and card‑holders across the country. With a culture that encourages curiosity, collaboration, and continuous learning, American Express consistently ranks among the top employers for fresh graduates seeking a fast‑paced, high‑impact career. The Data Analytics role is positioned within the Marketing Analytics team, where analysts translate complex data into actionable insights that shape campaign strategy, investment planning, and overall marketing effectiveness. As a fresher, you will work closely with senior analysts, product managers, and cross‑functional stakeholders to understand business problems, explore data sources, and deliver clear, data‑driven recommendations. This role offers a unique blend of analytical rigor, business acumen, and exposure to real‑world marketing initiatives. **Key Responsibilities** 1. Quickly grasp business problems, marketing objectives, and data sources to generate actionable insights. 2. Support analytics, measurement, and reporting across key marketing priorities such as target strategy, campaign performance, and investment planning. 3. Develop audience, cohort, market, and segment‑level diagnostics to identify opportunities and improve marketing effectiveness. 4. Partner with cross‑functional teams to translate business questions into structured analyses and deliver clear recommendations. 5. Conduct campaign measurement, test‑and‑control analysis, performance tracking, and financial impact assessment. 6. Streamline and automate analytical processes to improve scalability, consistency, and speed of insight delivery. 7. Prepare executive‑ready materials, including performance updates, marketing insights, and strategic recommendation presentations. 8. Maintain and enhance data visualisation dashboards using Tableau or Power BI. 9. Perform ad‑hoc analysis to support rapid decision‑making for marketing initiatives. 10. Continuously monitor industry trends and best practices to bring innovative analytical techniques to the team. **Tech Stack**: SQL, Python, Hive, SAS, Advanced Excel, Tableau, Power BI, VBA, and basic knowledge of cloud data platforms. **Growth Path**: Starting as a Data Analyst, high performers can progress to Senior Analyst, Analytics Lead, and eventually to Manager or Director of Marketing Analytics, with opportunities to move across product, finance, or strategy domains. **Why Join American Express?** The company offers a hybrid work model, competitive compensation, robust learning programs, and exposure to global best practices. Fresh graduates gain mentorship from seasoned professionals, work on high‑visibility projects, and develop a strong foundation in marketing analytics that is highly valued across industries.