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Analyst-Data Analytics (Agentic)

American Express · Posted Oct 14

Banking, credit card, payment network, and travel services

Gurugram, HR, IndiaFull-timeHybridMid Level₹12.0L–₹22.0L yearly59 applicants
BankingPaymentsCredit CardsFinancial ServicesPublic Company
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About the role

The Analytics, Investment Optimization and Marketing Enablement (AIM) team, part of the Global Commercial Services Marketing group at American Express, is the analytical engine that enables the Global Commercial Card & Non-Card business through data, analytics, decision science and AI-powered capabilities. This Gurugram-based role focuses on developing and applying advanced Data Science and Generative AI solutions across high-impact problems such as customer acquisition, engagement, targeting, personalization, product and portfolio analytics, marketing measurement and analytical productivity. The incumbent will apply LLMs, Retrieval-Augmented Generation, prompt engineering, agentic AI and other emerging AI techniques alongside traditional Data Science and Machine Learning approaches, collaborating with AIM, GCS Marketing, Product, Capabilities and Technology partners.

What you will do

  • Develop hands-on Generative AI and Data Science solutions to solve complex and unstructured business problems across GCS.
  • Design, build and experiment with LLM-powered solutions using techniques such as prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, semantic search and vector-based retrieval.
  • Develop and experiment with agentic AI workflows that can reason over context, leverage relevant data and tools, and support analytical and business decision-making.
  • Develop and apply evaluation approaches for GenAI solutions across dimensions such as response quality, relevance, consistency and business effectiveness, with appropriate consideration for responsible AI, controls and governance.
  • Apply Machine Learning and statistical techniques alongside Generative AI to develop fit-for-purpose solutions for customer acquisition, engagement, targeting, personalization, measurement and other business opportunities.
  • Explore structured and unstructured data from multiple sources to identify relevant signals and develop innovative approaches that transform data into actionable insights and AI-powered solutions.
  • Prototype, test and refine emerging GenAI techniques and collaborate with Technology, Capabilities and other partner teams, as appropriate, to support development of scalable solutions.
  • Explore emerging LLMs, GenAI techniques and frameworks and assess their applicability to relevant GCS business and analytical problems.
  • Work with business partners and other stakeholders to understand business needs, structure analytical problems and translate them into appropriate Data Science and GenAI approaches.
  • Define appropriate analytical measures and success metrics, evaluate results and communicate findings, limitations and recommendations clearly to technical and non-technical stakeholders.
  • Contribute to the development of reusable GenAI approaches, analytical assets and learnings that can support applications across AIM.
  • Demonstrate curiosity and willingness to challenge the status quo; bring innovative thinking to generate insights, alternatives and opportunities for business success.

Skills used in this role

PythonSQLMachine LearningStatistical ModelingSupervised LearningUnsupervised LearningGenerative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Prompt EngineeringEmbeddingsSemantic SearchVector-Based RetrievalAgentic AILangChainLangGraphLlamaIndexHugging FaceNatural Language ProcessingModel Fine-TuningParameter-Efficient Fine-TuningCommunicationProblem SolvingAnalytical Thinking

What the employer is looking for

  • Bachelor’s or Master’s degree in a quantitative or technical field such as Computer Science, Engineering, Mathematics, Statistics, Economics, Data Science, Artificial Intelligence or a related discipline.
  • 0–3 years of relevant experience in Data Science, Machine Learning, Generative AI or Analytics, with demonstrated hands-on experience developing Generative AI solutions through professional work, internships, academic research or substantial projects.
  • Strong programming skills in Python and working knowledge of SQL, with the ability to manipulate data, conduct analysis and develop Data Science/AI solutions.
  • Strong foundation in Data Science and Machine Learning concepts, including statistical modeling, supervised and unsupervised learning, model evaluation and experimentation.
  • Hands-on understanding of Large Language Models and core GenAI techniques such as prompt engineering and Retrieval-Augmented Generation (RAG), including concepts such as embeddings, semantic retrieval and using relevant data and context to improve LLM responses.
  • Understanding of approaches for evaluating GenAI solutions across dimensions such as response quality, relevance, consistency and reliability.
  • Strong analytical/conceptual thinking acumen with the ability to structure and solve unstructured and complex business problems.
  • Ability and curiosity to rapidly learn, experiment with and apply emerging AI techniques to practical business problems.
  • Excellent written and oral communication skills with the ability to articulate technical concepts and analytical findings clearly.

Preferred qualifications

  • Hands-on exposure to agentic AI concepts and workflows involving capabilities such as tool use, reasoning or multi-step orchestration.
  • Experience with GenAI/LLM frameworks and libraries such as LangChain, LangGraph, LlamaIndex, Hugging Face or equivalent tools.
  • Experience with vector-based retrieval, semantic search, advanced RAG techniques or LLM evaluation frameworks.
  • Familiarity with commercial and open-source LLMs and considerations involved in selecting appropriate models and approaches for different use cases.
  • Exposure to advanced GenAI techniques such as model fine-tuning, parameter-efficient fine-tuning or advanced retrieval approaches.
  • Experience working with unstructured data or Natural Language Processing techniques.
  • Familiarity with responsible AI principles and considerations related to applying AI within enterprise or regulated environments.
  • Interest in applying AI and GenAI capabilities to marketing, customer engagement, personalization, analytical productivity and business decision-making.

Benefits and support

  • Competitive base salaries
  • Bonus incentives
  • Support for financial-well-being and retirement
  • Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
  • Generous paid parental leave policies (depending on your location)
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counseling support through our Healthy Minds program
  • Career development and training opportunities

About American Express

American Express Company is a globally recognized multinational financial services corporation specializing in payment cards, travel-related services, and network banking. Founded in 1850, the company provides charge and credit cards, expense management products, and merchant services to consumers, small businesses, and large corporations worldwide. It operates a proprietary payments network known for its premium customer engagement and lifestyle rewards programs.

Industry
Banking
Company size
76800 employees
Founded
1850-03-18
Location
New York City, New York, USA
Funding stage
Public Company

Leadership

SJ
Stephen J. Squeri

Chairman and Chief Executive Officer

CL
Christophe Le Caillec

Chief Financial Officer

RR
Ravi Radhakrishnan

Chief Information Officer and Executive Vice President

MR
Monique R. Herena

Chief Colleague Experience Officer

ER
Elizabeth Rutledge

Chief Marketing Officer