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Data Scientist - US Bank

U.S. Bank

Los Angeles, California
  • Data Analytics
  • Data Scientist
  • Statistician
  • Business Intelligence
U.S. Bank
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Job Details


The Data Scientist on the Credit Risk Management team will support the development and projects of the group’s Advanced Analytics program. The program aims to leverage big data analytical techniques such as machine learning, artificial intelligence and neural network methodologies, natural language processing and others to extract insights from complex data and ultimately improve our risk management practices.

The Data Scientist will have the opportunity to be a part of building an impactful program from scratch and leverage their analytical and industry experience to solve challenging business problems. He or she will work in partnership with risk management teams throughout various businesses to identify data driven solutions to solve a diverse set of risk challenges.

The ideal candidate will not only have the necessary technical and communication skills but also possess a strong passion and aptitude for learning, an entrepreneurial mindset, and enjoy solving new and challenging problems.



  • Partner with risk management teams to evaluate business research opportunities.
  • Explore large and complex data structures to prepare data for analysis, develop experiments, test hypothesis and model structured data using advanced statistical and mathematical methods.
  • Translate analytical findings into actionable business insights and recommendations and effectively communicate these results to key stakeholders.
  • Collaborate with analytics and technology groups around the bank to ensure we stay a step ahead on emerging tools and resources to support advanced analytics and big data efforts.



Risk Management / Fraud Prevention

Primary Location

United States


1st - Daytime

Average Hours Per Week




  • University degree, ideally a Masters or higher, in statistics, mathematics, information systems, informatics, computer science, economics, or other quantitative disciplines.
  • Experience with advanced analytics, machine learning and/or artificial intelligence frameworks such as clustering, classification, random forest, ensemble, SVMs, neural networks, and etc as well as data science methodologies in general.
  • Experience coding in various languages (SAS, SQL, R, Python, Java, C etc) to explore and perform analytical analysis on large, disparate and complex data.
  • Demonstrated ability to develop relationships and communicate effectively between the business and analytics.
  • Experience in the banking, finance or risk management fields preferred.