Analyst-Data Science
The Analytics, Investment Optimization and Marketing Enablement (AIM) team – part of the Global Commercial Services Marketing group within American Express – is the analytical engine enabling the Global Commercial Card & Non-Card business. This role, based out of Gurugram, will be part of the SBS Engagement Analytics team, responsible for driving analytics across Spend, Lend and Beyond-the-Card engagement for U.S. Small Business customers.
The incumbent will develop analytical solutions and actionable insights to shape customer engagement and organic growth strategies. The role requires strong analytical problem-solving, SQL, statistical and modeling capabilities, and the ability to translate data into business recommendations.
- Own analytics for U.S. Small Business customer engagement across Spend, Lend and Beyond-the-Card priorities by identifying growth opportunities, developing customer-level insights, and recommending segmentation and targeting strategies to improve customer outcomes.
- Partner with Product, Marketing and business stakeholders to translate strategic questions into analytical plans, campaign design recommendations, success metrics and actionable business recommendations.
- Design and scale Test & Control, campaign measurement and performance diagnostic frameworks to quantify incremental impact, return on investment and optimization opportunities across targeting, messaging, offer design and channel strategy.
- Apply statistical, machine learning and modeling techniques—including regression, decision trees, clustering and XGBoost—using SQL, Python and large-scale customer, transaction and campaign datasets to solve engagement, propensity and targeting problems.
- Automate and standardize analytical processes, dashboards and measurement assets while exploring AI and GenAI capabilities to improve speed, accuracy, scalability, personalization and customer engagement.
Minimum Qualifications
- Master's Degree in a quantitative field (e.g., Engineering, Mathematics, Finance, Computer Science, Statistics, Economics).
- 0-2 years of professional experience in Data Science and Analytics.
- Strong proficiency in SQL and working with large datasets; experience with Python or similar analytical tools.
- Understanding of Test & Control, experimentation, campaign measurement and statistical techniques.
- Experience with modeling techniques such as XGBoost, clustering, decision trees and regression.
- Strong analytical and conceptual thinking to solve unstructured business problems.
Excellent written and verbal communication skills with the ability to translate analytics into actionable business recommendations.
Preferred Qualifications
- Experience in customer engagement, campaign analytics, personalization, cross-sell or growth analytics.
- Hands-on experience with GenAI, Prompt Engineering or RAG architectures is a plus.
- Strong stakeholder management skills with the ability to influence partners and drive action.