Analyst-Data Analytics

The GCS interview process typically starts with a timed online aptitude test covering quantitative, logical and verbal reasoning. Successful candidates move to a technical interview focused on Python, SQL, data‑manipulation and statistical concepts, often with live coding. The final HR round assesses cultural fit, communication skills and motivation. Overall difficulty is moderate; thorough preparation of coding fundamentals and business‑analytics scenarios is key.

American Express a collaborative, data‑driven culture where employees are encouraged to experiment and innovate. The division offers clear growth pathways, regular upskilling sessions and a healthy work‑life balance supported by flexible hybrid arrangements.

Bachelor's degree in a quantitative discipline such as Economics, Finance, Accounting, Statistics, Data Analytics, Engineering, Computer Science or Artificial Intelligence. Minimum aggregate of 60% (or CGPA 6.0/10). No active backlogs at the time of joining. Graduation batch 2025 or 2026. Strong analytical mindset and proficiency in Python and SQL are mandatory.

Round 1: Online aptitude & logical reasoning test → Round 2: Technical interview (Python, SQL, data analytics concepts) → Round 3: HR interview (fitment, culture, motivations)

American Express is a global financial services leader with a 175‑year legacy of innovation, trusted by millions of customers worldwide. Within the organisation, Global Commercial Services (GCS) powers the commercial side of the business, delivering payment, cash‑flow and working‑capital solutions to enterprises ranging from small retailers to Fortune‑500 corporations. GCS combines deep industry expertise with cutting‑edge technology to help merchants grow, while upholding the company’s core values of integrity, customer focus and responsible growth. The division is known for its collaborative culture, strong emphasis on data‑driven decision making, and a commitment to employee development through continuous learning and mentorship programmes. The Analyst‑Data Analytics role sits in the Sales Enablement Organization, a specialised team that accelerates commercial growth by providing training, tools and insights. As a technical sales‑ops analyst, you will design, build and maintain automation solutions that streamline operational processes across the US SME channel. You will work closely with sales, marketing, technology and analytics stakeholders to identify gaps, develop data‑rich models, and deliver actionable insights that drive revenue and improve efficiency. This is an ideal position for a fresh graduate with strong analytical instincts, programming skills and a passion for solving real‑world business problems. Key responsibilities include: 1. Design and implement end‑to‑end automations for operational workflows across US SME sales channels. 2. Partner with SME Sales, AD organization, Oneforce Capabilities, Tech, Control Management and CEG to ensure alignment and successful rollout. 3. Conduct deep‑dive analysis to uncover process gaps, risks and opportunities, translating findings into actionable recommendations. 4. Develop, validate and deploy automated solutions with minimal manual intervention, leveraging Python, SQL and Hive. 5. Apply statistical modelling and data‑mining techniques to support decision‑making and performance tracking. 6. Build and maintain dashboards and visualisations using Tableau, Power BI or similar tools for senior leadership. 7. Continuously evaluate existing processes, challenge the status quo and propose innovative improvements. 8. Document workflows, create SOPs and train end‑users on new automated tools. 9. Monitor solution performance, troubleshoot issues and iterate for optimisation. 10. Contribute to cross‑functional projects, sharing insights with analytics, marketing and product teams. Tech stack: Python (pandas, scikit‑learn), SQL, Hive, PySpark, Unix scripting, Excel/VBA, Tableau/Power BI, Salesforce, Hadoop/Spark, Google Cloud, ServiceNow, Confluence and SharePoint. Growth path: Starting as an Analyst, high performers can progress to Senior Analyst, Data Analytics Lead, or Manager – Data Analytics within 2‑3 years, with opportunities to move into product analytics, data science or sales‑ops leadership roles. The role offers exposure to global stakeholders, complex data environments and strategic business initiatives, laying a strong foundation for a long‑term career in analytics and commercial operations. Why join GCS? You will be part of a world‑class financial institution that values innovation, diversity and employee well‑being. The hybrid work model provides flexibility, while the company’s robust learning ecosystem (internal trainings, certifications, mentorship) ensures continuous skill development. Competitive compensation, performance‑linked bonuses and comprehensive benefits make it an attractive destination for ambitious freshers seeking to make a tangible impact on a global scale.