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Salary
≈ $11k – $22k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Junior · 1+ year exp

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Oct 5, 2026. American Express scores A on the Alion truth index.

Overview
Company
Impact
Profile match
American Express is a New York financial services company founded in 1850 as an express freight business that became a payments network and card issuer. Unlike the four-party networks it competes with, it issues most of its own cards and operates its own network, which lets it earn merchant discount revenue as well as interest and annual fees, and supports a premium rewards proposition built on travel and lounge access. Its business spans consumer and small business cards, corporate payments, merchant acquiring and travel services, and it is a component of the Dow Jones Industrial Average.

The Analytics, Investments and Marketing Enablement (AIM) team within Global Commercial Services Marketing (GCSM) powers customer acquisition, engagement, and retention through data, advanced analytics, and AI.

Within AIM, the Customer Experience Optimization (CXO) Personalization - GCS Digital Acquisitions team is focused on building scalable, intelligent personalization for SME customers across acquisition channels-including website and application experiences.

This team sits at the intersection of AI/GenAI, advanced analytics, and digital product, with a mandate to build AI-native personalization capabilities. The team is responsible for shaping how we deliver relevant, context-aware experiences to SBS and Corporate prospects in real time, with a strong focus on building scalable systems and capabilities, not just analysing outcomes.

In this role, you will focus on executing personalization strategies and developing analytical solutions that improve customer engagement and conversion. You will work closely with cross-functional partners to embed personalization into digital experiences and support the delivery of scalable, data-driven use cases.

Shift Time- 1:30 PM - 9:30 PM

Personalization & Digital Experience Support

  • Assist in executing personalization strategies across digital touchpoints (e.g., website, landing pages, application flows).
  • Analyze customer behavior and contextual data to support targeted messaging, content, and offers.
  • Work with product and engineering teams to help implement personalization features on digital platforms.
  • Support development of personalization use cases using basic machine learning or GenAI techniques (e.g., segmentation, next-best-action).
  • Help with data preparation, model inputs, and testing under guidance.
  • Contribute to experimentation and evaluation of AI-driven features.
  • Work with structured and unstructured data to generate insights.
  • Build queries, dashboards, and basic analytical models.
  • Contribute to reusable code and analysis pipelines with guidance.
  • Assist in monitoring model performance and reporting key metrics.

Data Analysis & Solution Development

Problem Solving & Insights

  • Break down business problems into smaller analytical tasks with support.
  • Generate insights from data and present findings clearly.
  • Support measurement and analysis of personalization initiatives.

Minimum Qualifications

  • Master’s degree in a quantitative discipline such as Engineering, Mathematics, Computer Science, Physics, Finance, or Economics.

  • 1+ years of experience in data science, advanced analytics, machine learning, decision science, or related quantitative roles.

  • Strong programming skills in Python and SQL, with hands-on experience developing machine learning models and analytical solutions.

  • Strong communication and interpersonal skills, with the ability to deliver clear insights and collaborate across teams.

Preferred Qualifications

  • Experience developing AI/ML, NLP, or Generative AI/LLM-based solutions.

  • Experience building scalable analytical workflows and production-ready solutions.

  • Prior experience in marketing analytics, commercial analytics, personalisation or digital data.

  • Familiarity with web/app analytics tools or experimentation platforms.

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