Analyst-Data Analytics (Python, SQL, Gen AI)

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.
Bachelor's in engineering or Master’s degree in a quantitative field (e.g., Statistics, Engineering, Physics, Mathematics and Economics) or PhD is required.
Hands on exposure to data science tools & techniques such as Big Data, PySpark, Hive, Scala, Python is required.
Ability to learn and quickly adapt around ever evolving analytics landscape is preferred.
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.
Effectively engage and deliver results in a cross-functional collaborative environment, i.e., in partnership with key stakeholders including the functional channel owners, the business partners/end-users of data science solutions and technology partners.
Explore usage and implementation of data mining techniques, including regression analysis, clustering, and decision trees.
Explore and integrate emerging AI and GenAI techniques - such as intelligent customer journey optimization, semantic modeling and automated insights to enhance targeting precision and analytical productivity.
Exceptional execution skills – be able to resolve issues, identify opportunities, define success metrics, and make things happen.
Prioritizing efforts to help the team focus on the most impactful opportunities.
High degree of organization, individual initiative, and personal accountability.

Work arrangement
Hybrid