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American Express
American Express
B2BBankingFinance
American Express is a global financial services company operating across banking, finance, and B2B payments. Its business includes consumer, business, and corporate credit cards; payment and merchant services; savings accounts, certificates of deposit, and personal loans; as well as rewards, travel programs, corporate payment solutions, financial education, security services, and cardmember and merchant support.
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Data Science Analyst, Machine Learning and GenAI

Build machine learning, generative AI, and recommendation solutions for American Express customer servicing. Analyze customer and operational data to strengthen personalization and improve how service teams work.

INIndiaHybridFull-timeMiddleSeniorEnglish RequiredData Scientist
PythonSQL

Description

  • Develop analytical solutions, predictive models, and decisioning approaches to improve customer service, personalization, colleague effectiveness, and operations.
  • Analyze customer, behavioral, interaction, and operational data to find patterns and opportunities.
  • Create features, test hypotheses, and turn findings into practical insights and solutions.
  • Build and assess machine learning and generative AI solutions through modeling, experimentation, and validation.
  • Contribute to agentic AI workflows, transformer-based recommendations, conversational AI and LLM applications, and personalization or next-best-action solutions.
  • Help design and analyze experiments, measuring model quality, business impact, and areas for improvement.
  • Write strong analytical code and partner with data, technology, and platform teams to implement, deploy, monitor, and improve decision science solutions.
  • Collaborate across teams, communicate findings clearly, and translate technical results into useful recommendations.
  • Stay informed about developments in machine learning, generative AI, recommendation systems, and decision intelligence.
  • Evaluate relevant methods and help establish reusable practices across GSDS.

Requirements

  • Master’s degree in a quantitative discipline such as engineering, computer science, mathematics, statistics, economics, or finance.
  • Relevant academic, internship, or professional experience in data science, machine learning, advanced analytics, or another quantitative field.
  • Proficiency with Python, SQL, or similar analytical tools.
  • Foundational experience developing machine learning models, such as tree-based, regression, classification, or clustering models.
  • Coursework, project work, or other exposure to large language models, generative AI, or modern deep learning.
  • Strong analytical and conceptual thinking, including the ability to structure problems, learn quickly, and navigate ambiguity.
  • Clear written and verbal communication skills and the ability to collaborate across functions.
  • Preferred: Exposure to agentic AI frameworks, transformer architectures, transformer-based recommendations, conversational AI, LLM applications, embeddings, or semantic modeling.
  • Preferred: Exposure to personalization, recommendation systems, next-best-action, optimization, experimentation, or customer decisioning.
  • Preferred: Project or work experience with structured or unstructured data and analytical or machine learning solutions.
  • Preferred: Familiarity with model or AI evaluation and basic productionization, monitoring, MLOps, or LLMOps concepts.
  • Preferred: Interest in customer servicing and connecting technical work to measurable customer and business outcomes.
  • Successful completion of a background verification check, subject to applicable laws and regulations.

Benefits

  • Competitive base pay.
  • Bonus incentives.
  • Support for financial well-being and retirement.
  • Comprehensive medical, dental, vision, life insurance, and disability coverage, depending on location.
  • Flexible hybrid, onsite, or virtual work arrangements, depending on the role and business needs.
  • Generous paid parental leave, depending on location.
  • Complimentary access to global onsite wellness centers staffed by nurses and doctors, depending on location.
  • Free, confidential counseling through the Healthy Minds program.
  • Career development and training opportunities.

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