Senior Data Scientist- Fixed Income Pricing

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New York, NY

Posted Jan 5, 2017 - Requisition No. 56351

Bloomberg L.P. revolutionized the financial industry 35 years ago by introducing the power of technology. We provide transparency to the ever-changing fixed income market through high quality pricing for millions of securities each day. Our use of robust data driven models separates us from the competition. We work in a unique environment where you will own a project from beginning to end. Your daily routine will involve working collaboratively to understand clients’ needs and research strategies to find the appropriate solutions. Our team will provide you a rare opportunity to work on projects that span various asset classes. Finally, you will gain familiarity with trade and other market data and build expertise in the fixed income market domain.

We’ll trust you to

  • Drive projects via conceptual planning and design of solutions to open-ended problems by leveraging domain expertise often under aggressive deadlines
  • Devise production quality software implementation of pricing algorithms
  • Prototype and implement pricing solutions
  • Interact regularly with product managers to understand and interpret business goals
  • Collaborate with peers on code reviews, integration with system level software and production rollout process
  • Analyze market data to identify signals to help build systems that satisfy business goals
  • Review and improve quality and performance of pricing systems on a continual basis

You’ll need to have

  • Graduate level degree or relevant experience in advanced applied mathematics, statistics, operations research, engineering or similar
  • At least two years of financial industry experience
  • Experience with C/C++ and Python/R in a production environment
  • Proficiency in time-series modeling and Bayesian statistics
  • Experience with debugging and maintaining large code bases
  • Expertise in following areas is highly desired: Fixed income mathematics, optimization, credit modeling, analysis of large financial datasets, numerical analysis

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