Analyst-Data Science

AMERICAN EXPRESS

0 - 3 years

18 - 20 Lacs

gurugram

Posted:-1 days ago| Platform:

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Skills Required

computer science career development automation data modeling finance analytical data quality analytics monitoring sql

Work Mode

Work from Office

Job Type

Full Time

Job Description

The Analyst will be part of the Global Spend Insights & Analytics team, supporting the development and maintenance of Global Spend/Industry/Merchant dashboards and contributing to strengthening risk control with enhanced levels of documentation and analytic solutions, such as anomaly detection algorithms.

Key Responsibilities-

Support the ownership of AXP Spend Dashboards, including data quality checks, automation, synthesis of results, and clear communication of insights.
Contribute to strengthening risk control by developing documentation and implementing analytic solutions (e.g., anomaly detection logic), including refinement, monitoring, and stakeholder communication.
Work with large and complex datasets to extract meaningful insights; conduct analyses to inform business decisions and provide actionable recommendations.
Partner with cross-functional teams to ensure data integrity, business relevance, and actionable outputs.
Present analyses and findings effectively to a range of audiences, including both technical and non-technical stakeholders.

Qualifications -

Proficiency in SQL, Hive, Python, Pyspark, Machine Learning Techniques
Working experience in reporting (i.e. data visualization, KPIs tracking, scorecards) is a plus
Intellectual curiosity about the business trend and P&L management. Working experience in Finance / Corporate Planning is a plus although not required
Excellent problem-solving and communication skills, with the ability to explain complex data topics to non-technical audiences
Experience with data modeling, anomaly detection, or similar analytical techniques
Bachelor s degree required and master s degree preferred in following areas: Statistics, Economics, Mathematics, Engineering, Finance, Computer Science, or related quantitative fields

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