Senior Associate, Data Management & Quantitative Analysis

The Bank of New York Mellon-posted 2 months ago
Mid Level
Pittsburgh, PA
5,001-10,000 employees
Securities, Commodity Contracts, and Other Financial Investments and Related Activities
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At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators and champions of inclusion, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We're seeking a future team member for the role of Senior Associate, Data Management & Quantitative Analysis to join our Structured Debt Client Platform team. This role is located in Houston, TX or Pittsburgh, PA.

  • Work with internal and external datasets and client reference data to provide analysis in the development of statistical, financial, and/or econometric models for analyzing asset performance, securities data, derivative pricing, risk exposure, or other sophisticated concepts.
  • Provide analytical support and prepare drafts of standard and ad hoc reports for the assigned area.
  • Support assigned area with advanced statistical and quantitative analyses, serving as a resource to less experienced colleagues.
  • Use technology tools such as SQL, querying, and macro development to extract data, run models, identify exceptions, and take corrective action.
  • Bachelor's degree or the equivalent combination of education and experience; advanced degree in quantitative analysis preferred.
  • 3-5 years of experience preferred.
  • Experience in quantitative finance and technology preferred.
  • Strong understanding of relevant processes and products in the assigned area, with the ability to interpret findings and translate complex technical concepts to non-technical audiences.
  • Strong skills in SQL, querying, macro development, and familiarity with programming or system configuration to set up sophisticated models or algorithms.
  • Highly competitive compensation
  • Benefits and wellbeing programs
  • Access to flexible global resources and tools
  • Generous paid leaves, including paid volunteer time
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