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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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Senior Data Science Analyst

Build predictive models that inform American Express decisions across risk, fraud, and marketing. Analyze large datasets to uncover business insights and support profitable customer outcomes.

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

Tavsif

  • Build, deploy, and validate predictive models.
  • Apply models within economic frameworks to support profitable decisions in risk, fraud, and marketing.
  • Learn how American Express operates and what factors shape its business decisions.
  • Analyze large datasets to uncover business insights and develop innovative solutions.
  • Use the American Express network to make decisions more informed and relevant.
  • Create improved approaches using big data and machine learning.
  • Present and organize findings across prospect and customer domains for leaders and key partners.
  • Track developments in finance, payments, and analytics.

Talablar

  • MBA or a master’s degree in economics, statistics, computer science, or a related field.
  • 24–48 months of experience in analytics or big data workstreams.
  • Work effectively as part of a team.
  • Drive project deliverables toward business results.
  • Strong communication and interpersonal abilities.
  • Solve problems creatively, learn quickly, and work independently on complex, unstructured initiatives.
  • Collaborate with cross-functional business partners around the world.
  • Experience with SAS, R, Python, Hive, Spark, and SQL.
  • Knowledge of supervised and unsupervised methods, including active and transfer learning, neural models, decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, MapReduce, and feature engineering.
  • Employment is contingent on successfully completing a background verification check, subject to applicable laws and regulations.

Imtiyozlar

  • Competitive base salary.
  • Bonus incentives.
  • Support for financial well-being and retirement.
  • Medical, dental, vision, life insurance, and disability coverage, depending on location.
  • Flexible hybrid, onsite, or virtual work arrangements, depending on 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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