Analyst-Data Science at American Express in Gurgaon, Haryana, IN

The AIM (Analytics, Investment & Marketing Enablement) team – a part of GCS Marketing – is the analytical engine that enables the Global Commercial Services portfolio of American Express. Accelerating growth momentum, increasing profitability, and strengthening our value proposition are key objectives for this organization.

This Analyst – Data Science role, based out of India, will join the Prospect Cross-functional team within AIM and execute analytical workstreams supporting prospect targeting and acquisition initiatives. Leveraging a broad analytical toolkit—including advanced machine learning, predictive modeling, optimization, and Generative AI—the role supports the end-to-end development of scalable analytical solutions that enhance targeting precision, engagement effectiveness, and marketing ROI.

This role provides an opportunity to build next-generation AI-powered capabilities across prospect enrichment, intelligent targeting, lead prioritization, and decision support by combining advanced analytics with modern Generative AI techniques. Working closely with data scientists, product managers, engineers, and business stakeholders, the Analyst will develop scalable analytical solutions that accelerate data-driven decision making while maintaining the highest standards of Responsible AI and model governance.

Responsibilities

• Execute analytical and data science solutions to solve business problems using statistical techniques, machine learning, and modern Generative AI approaches.
• Develop, test, and maintain analytical models and AI-enabled data products—including predictive models, prospect scoring, prioritization, matching, enrichment, and intelligent decision-support capabilities—to improve targeting and acquisition effectiveness.
• Design, build, and evaluate Generative AI workflows, including Retrieval-Augmented Generation (RAG), embedding-based retrieval, semantic search, prompt engineering, structured outputs, and LLM-powered applications, selecting appropriate approaches based on business requirements, solution quality, scalability, latency, cost, and governance considerations.
• Design and execute experiments to evaluate prompting strategies, retrieval configurations, model selection, and workflow architectures, continuously optimizing solution quality, response accuracy, operational efficiency, and business impact.
• Perform data extraction, preparation, feature engineering, and data quality validation using large-scale datasets to support AI/ML model development and analytical initiatives.
• Apply statistical and machine learning techniques to improve model performance through experimentation, feature refinement, validation, and continuous model optimization using established best practices.
• Collaborate with product, engineering, and business stakeholders to support the implementation, deployment, monitoring, and continuous improvement of analytical and Generative AI solutions within business workflows.
• Evaluate AI and GenAI solution performance using quantitative and qualitative evaluation techniques, including model performance metrics, retrieval quality, response accuracy, prompt robustness, business outcome measures, and production monitoring.
• Communicate analytical findings, model outputs, and business insights clearly through presentations and technical documentation for both technical and non-technical stakeholders.
• Ensure compliance with Responsible AI principles, model governance, data integrity, explainability, bias assessment, prompt safety, monitoring, audit readiness, and enterprise risk management standards throughout the analytical development lifecycle.

Qualifications

• Degree in a quantitative field preferred, such as Engineering, Mathematics, Computer Science, Finance, Economics, Statistics, or a related discipline.
• 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 working knowledge of Hive and/or PySpark in large-scale data environments, hands-on experience developing machine learning models end-to-end, and familiarity with software engineering best practices including Git-based version control.
• Demonstrated hands-on experience building or experimenting with LLM-based applications, including Retrieval-Augmented Generation (RAG), prompt engineering, semantic search, embeddings, structured outputs, or AI-powered assistants.
• Knowledge of supervised machine learning techniques (e.g., gradient boosting, tree-based models, regression, clustering) and statistical techniques such as hypothesis testing, multivariate testing, ANOVA, and model evaluation methodologies.
• Exposure to AI agent frameworks, tool/function calling, vector databases, LLM orchestration frameworks (e.g., LangChain, LlamaIndex, DSPy), context management, or workflow automation is a plus.
• Familiarity with modern ML/AI development frameworks, open-source libraries, prompt lifecycle management, and evaluation frameworks.
• Strong analytical and problem-solving skills, with the ability to execute well-defined analytical tasks accurately and efficiently.
• Demonstrated ability to manage assigned work independently while collaborating effectively within a cross-functional team.
• High attention to detail, intellectual curiosity, and an experimentation mindset with the ability to evaluate solutions objectively and iterate based on evidence.
• Strong written and verbal communication skills, with the ability to clearly explain analytical findings and support stakeholder discussions.
• Familiarity with Responsible AI principles, including explainability, bias and fairness assessment, hallucination mitigation, prompt safety, model monitoring, evaluation, audit readiness, and GenAI risk management practices.

About the Team

We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:

• 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

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.

Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

About the Company

At American Express, our culture is built on a 175-year history of innovation, shared valuesand Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.