About this role
The AIM (Analytics, Investment & Marketing Enablement) team – a part of GCS Marketing– is the analytical engine that enables Global Commercial business portfolio of American Express. Accelerating growth momentum, increasing profitability, and powering up our value proposition are key objectives for this organization. The team enables GCS Marketing business by providing actionable insights to drive business strategy and growth.
This Analyst (Band 30) role would be based in Gurgaon, IN and would be focused on driving sentinel Analytics spanning across channels and product offerings from Amex. The incumbent will be responsible for driving innovative analytical solutions and strategies that helps in gaming prevention thereby driving profitable acquisitions for the commercial business. S/he will be challenged with designing and creating world class prospect marketing analytics by leveraging machine learning and advanced methodologies.
A very important focus for the role shall be leveraging data science, quantitatively determining the value, deriving insights, and then assuring the insights are leveraged to create positive impact that cause a meaningful difference to the business.
Minimum Qualifications
- Bachelor's in engineering or Master’s degree in a quantitative field (e.g., Statistics, Engineering, Physics, Mathematics and Economics) or PhD is required.
- Proficiency & experience in applying cutting edge statistical and machine learning techniques to business problems and leverage external thinking (from academia and/or other industries) to develop best in class data science solutions.
- Strong communication and interpersonal skills, and ability to build and retain strong working relationships.
- Strong analytical/conceptual thinking acumen to solve business problems and articulate key findings to senior leaders/stakeholders in a succinct and concise manner.
- Ability to project-manage effectively, manage several concurrent projects through collaboration across teams/geographies.
Preferred Qualifications
- Familiarity and interest in applying emerging AI and Gen AI capabilities to improve digital targeting outcomes, with LLM and RAG exposure
- Experience with building ML models like XGBoost, K-Means, etc with proficiency in analytical tools such as SQL, Python, or similar; knowledge of digital analytics or experimentation frameworks is a plus.
- Ability to learn and quickly adapt around ever evolving analytics landscape is preferred.