Analyst-Data Analytics

American ExpressGurugram, HaryanaHybridFull-timeMid level, 2–5 yearsListed 1 hour ago

Apply now

About this role

The Global Servicing (GS) organization delivers extraordinary customer care to Card Members, merchants and commercial clients around the world, while providing world-class credit, collections and fraud services.

The Risk MIS & Analytics team supporting Fraud Operations provides analytical, reporting and decision-support capabilities to enable effective management of fraud operations. The team partners with Fraud Operations and cross-functional stakeholders to deliver timely, accurate and actionable MIS, identify emerging trends and information gaps, and enable data-driven operational decisions.

This position will be based out of the American Express Service Center in Gurgaon, India and will work with stakeholders across markets and time zones.

Purpose of the Role:
The Analyst will be responsible for MIS, reporting and analytics supporting Fraud Operations, including operational performance measurement, trend analysis, executive reporting and development of scalable reporting capabilities.

- Bachelor’s degree or equivalent, preferably in a quantitative field; postgraduate qualification in a quantitative discipline is an advantage.
- Preferably 4+ years of experience, including at least 2 years in quantitative business analysis, MIS, analytics or data science involving large datasets.
- Strong quantitative, analytical, problem-solving and data visualization capabilities.
- Excellent programming skills in Hive/Python/SQL/ Tableau, with a good understanding of Big Data ecosystems.
- Experience with Tableau, QlikView or similar BI/visualization tools is an advantage.
- Advanced knowledge of Microsoft Excel and PowerPoint; working knowledge of Word, Access and Project.
- Ability to translate business information requirements into scalable MIS, reporting and analytical solutions.
- Strong communication, stakeholder management and project management skills.
- Ability to independently manage multiple priorities and deliver within tight timelines.