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JobDescription : The Role: Analyst, Global Research & Design The Location: New York City The Team: Global Research & Design, Americas
The Global Research & Design group at S&P Dow Jones Indices is looking for a quantitative research analyst with a strong background in mathematics, computer programming, and machine learning to support the Americas region research team. The team is responsible for the conceptualization and design of new indices for S&P Dow Jones Indices, and the creation of research to provoke thinking on new passive investment concepts. The team serves as an innovator and thought leader within and outside the organization.
This role handles all aspects to support the research and design for equity and multi-asset indices and involves generating investment ideas, gathering and cleansing data, back-testing strategies, running index analytics, finalizing index methodologies, preparing presentations, and publishing research papers. This role will also research and test alternative data using machine learning.
Perform portfolio construction, back-testing, and quantitative analysis of various index strategies including smart beta, multi-asset, sustainability, thematic, etc.
Understand and implement machine learning into index design.
Support lead analysts on data gathering, data quality assurance, and index analytics.
Assist lead analysts in the creation of research publications, documentations, and other presentation collateral.
Create and support automation tools and process used by the wider team.
Coordinate with the rest of the Global R&D team, as well as other functional groups including Product Management, Sales, Marketing, Channel, and Index Management.
Must be able to manage multiple concurrent projects and deadlines.
Must be able to clearly communicate to a variety of both internal and external clients.
Minimum 2+ years of professional experience in a financial services or analytics role.
Bachelor's degree or equivalent in a quantitative field such as Finance, Mathematics, Data Science, Computer Science, Economics, or Engineering. Ph.D. preferable.
Progress towards or completion of CFA charter exams desirable.
Experience using financial data applications e.g. FactSet, Morningstar, Bloomberg, Reuters.
Programming skills in Python, MATLAB, and/or R.
Experience using machine learning and natural language processing to test/analyze alternative and unstructured data.
Hands-on experience with portfolio back-testing and simulation.
Internal Number: 6188985
About S&P Global
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