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.