Associate Director - Index Management Research
- Employer
- S&P Global
- Location
- New York, USA
- Salary
- Competitive
- Closing date
- Oct 31, 2019
View more
- Job Function
- Other
- Industry Sector
- Finance - General
- Employment Type
- Full Time
- Education
- Bachelors
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JobDescription :
The Role: Associate Director - Index Management Research
The Location: New York City
The Team: IMPG, Americas
The Impact:
S&P Dow Jones Indices is searching for an industry expert to lead the evolution of the global approach to measuring industry classifications. The Index Management & Production Group (IMPG) is looking for an Associate Director, Index Management Research with a strong background in mathematics, computer programming, and machine learning to support the high visibility US region operations team. This team is responsible for overseeing the most important and iconic indices at S&P Dow Jones indices-the S&P 500 and Dow Jones Industrial Averages along with many derivative indices. This unique role will also support and help evolve a group of cutting edge, innovative new economies indices leveraging Kensho's proprietary natural language processing (NLP) platform and machine learning algorithms. The Associate Director will also survey, analyze and interact with analysts across the various sectors of the equity markets keeping abreast of changes and suggesting updates to the Global Industry Classification Standard (GICS) which is recognized as a the leading industry classification standard.
Your Impact:
This role will allow for a broad portfolio of duties with responsibilities split evenly amongst machine learning indices, US indices, GICS research and general index research. This is a high visibility role as the analyst will be a subject matter expert for several index committees and will have the opportunity to contribute to new passive methodology best practices concepts and innovation.
Responsibilities:
Basic Qualifications:
Preferred Qualifications:
The Role: Associate Director - Index Management Research
The Location: New York City
The Team: IMPG, Americas
The Impact:
S&P Dow Jones Indices is searching for an industry expert to lead the evolution of the global approach to measuring industry classifications. The Index Management & Production Group (IMPG) is looking for an Associate Director, Index Management Research with a strong background in mathematics, computer programming, and machine learning to support the high visibility US region operations team. This team is responsible for overseeing the most important and iconic indices at S&P Dow Jones indices-the S&P 500 and Dow Jones Industrial Averages along with many derivative indices. This unique role will also support and help evolve a group of cutting edge, innovative new economies indices leveraging Kensho's proprietary natural language processing (NLP) platform and machine learning algorithms. The Associate Director will also survey, analyze and interact with analysts across the various sectors of the equity markets keeping abreast of changes and suggesting updates to the Global Industry Classification Standard (GICS) which is recognized as a the leading industry classification standard.
Your Impact:
This role will allow for a broad portfolio of duties with responsibilities split evenly amongst machine learning indices, US indices, GICS research and general index research. This is a high visibility role as the analyst will be a subject matter expert for several index committees and will have the opportunity to contribute to new passive methodology best practices concepts and innovation.
Responsibilities:
- Support lead analysts on data gathering, data quality assurance, and index analytics for the iconic S&P 500 and Dow Jones Averages.
- Analyze industry trends for GICS sectors and Kensho New Economies and suggest potential methodology or structural changes.
- Perform index research and analysis to help inform committee decision making on strategies and index methodology changes
- Analyze and implement machine learning and NLP logic into index design for the S&P Kensho index family
- Perform ad hoc index construction and quantitative analysis of various index strategies to identify product enhancement opportunities
- Create and support automation tools and process used by the wider Index Management and Production team.
- Coordinate with the Global IMPG to ensure adoption of new practices and processes.
Basic Qualifications:
- 5+ years of experience
- Bachelor's Degree
- Superior computer skills in Excel, Word, databases and related applications
- Understanding of global financial markets
- Must be able to work independently on multiple projects with minimal direction or supervision
- Must be able to demonstrate excellent analytical and quantitative capabilities to solve problems in a timely and insightful manner
- 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.
- Excellent written and verbal communication skills and the ability to coordinate work done by multiple people and / or groups.
Preferred Qualifications:
- CFA or Advanced degree in business, mathematics, economics, or finance preferred
- Professional experience in index/portfolio management or a similar role.
- Experience with corporate action research, stock-screening, index rebalancing
- Understanding of how indices are used and the impact corporate events/rebalance changes have on both indices and financial portfolios.
- Multi-asset experience preferred
- Knowledge of programming languages such as Python, VBA, SQL, or Matlab is considered an asset
- Experience using financial data applications e.g. FactSet, S&P Capital IQ, Reuters.
- Experience using machine learning and natural language processing to test/analyze alternative and unstructured data.
- Hands-on experience with portfolio back-testing and simulation
For further details on Kensho New Economies Indices:
S&P Kensho New Economies Indices
For the latest GICS structure changes:
https://my.spindices.com/documents/indexnews/announcements/20171115-615951/615951_gicsfinalrevisions15nov2017-final.pdf?force_download=true
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