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American Express
American Express
B2BBank ishiMoliya
American Express bank ishi, moliya va B2B to‘lovlari sohalarida faoliyat yurituvchi global moliyaviy xizmatlar kompaniyasidir. Kompaniya faoliyati jismoniy shaxslar, biznes va korporativ mijozlar uchun kredit kartalari; to‘lov va savdogarlarga xizmat ko‘rsatish xizmatlari; jamg‘arma hisobvaraqlari, depozit sertifikatlari va shaxsiy kreditlar; shuningdek, mukofotlar, sayohat dasturlari, korporativ to‘lov yechimlari, moliyaviy ta’lim, xavfsizlik xizmatlari hamda karta egalari va savdogarlarni qo‘llab-quvvatlashni o‘z ichiga oladi.
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Kompaniyadagi ish o‘rinlari

Senior Data Science Analyst, Machine Learning and GenAI – American Express, Gurugram Hybrid

Senior Analyst developing machine learning, GenAI, and decision-science solutions for American Express servicing. The role covers predictive modeling, recommendations, experimentation, and production-ready AI capabilities.

INHindistonGibridTo‘liq stavkaSeniorTalab Qilinadigan Til: inglizchaMa’lumotlar tahlilchisi
PythonSQL

Tavsif

  • Create analytical solutions, predictive models, recommendation systems, and decisioning methods that improve servicing, personalization, colleague effectiveness, and operational performance.
  • Analyze large customer, behavioral, interaction, and operational datasets to uncover opportunities, engineer features, test hypotheses, and turn findings into practical solutions.
  • Develop and assess machine learning and GenAI solutions using suitable modeling, experimentation, and validation methods.
  • Support Agentic AI workflows, transformer-based recommendations, Conversational AI and LLM applications, and advanced personalization or next-best-action initiatives.
  • Design experiments and performance measures to evaluate AI quality, model effectiveness, business impact, and opportunities for ongoing improvement.
  • Produce robust analytical code and collaborate with data, technology, and platform teams on productionization, monitoring, and continuous enhancement of Decision Science solutions.
  • Build cross-functional partnerships, explain analytical findings clearly, and convert technical results into actionable recommendations.
  • Track developments in machine learning, GenAI, recommendation systems, and decision intelligence while testing relevant methods and sharing reusable practices across GSDS.

Talablar

  • Master’s degree in a quantitative discipline such as engineering, computer science, mathematics, statistics, economics, or finance.
  • At least two years of professional experience in data science, machine learning, advanced analytics, or a related quantitative field.
  • Proficiency in Python, SQL, or comparable analytical tools, with experience developing models such as tree-based, regression, classification, or clustering techniques.
  • Exposure to LLMs, GenAI, or modern deep learning, together with a strong interest in emerging AI capabilities.
  • Strong analytical and conceptual reasoning, including the ability to address complex, unstructured business problems.
  • Clear written and verbal communication skills and the ability to work effectively with cross-functional partners.
  • Practical exposure to Agentic AI frameworks, transformer architectures, transformer-based recommendation systems, Conversational AI, LLM applications, embeddings, or semantic modeling.
  • Experience with personalization, recommendation systems, next-best-action, optimization, experimentation, or customer decisioning.
  • Experience processing and analyzing large structured or unstructured datasets and converting models into scalable analytical solutions.
  • Understanding of model and AI evaluation, productionization, monitoring, or MLOps and LLMOps concepts.
  • Curiosity about customer servicing and the ability to connect technical work with measurable customer and business results.

Imtiyozlar

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

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