Investment Risk Analytics Data Engineer Investment Risk Analytics Data Engineer …

BNY Mellon
à New York, NY, États-Unis
CDI, Plein-temps
Dernière candidature, 13 janv. 22
BNY Mellon
à New York, NY, États-Unis
CDI, Plein-temps
Dernière candidature, 13 janv. 22
Investment Risk Analytics Data Engineer
Reporting into the Head of Investment Risk Analytics, the Investment Data Specialist will be integral part of the newly created CRO Investment Risk's team. The Investment Risk Management team has Risk oversight of all investment management activity across the company, executing on our goal of full triangulation of risk management, providing dedicated senior risk coverage of our Investment Management business and other investment activities.

Position Summary
  • Facilitate the creation and management of a central Investment risk analysis and reporting platform to aggregate risk, performance and liquidity metrics data in a timely, transparent and consistent framework for a large investment management complex
  • Working within a risk analytics and data team, and cooperatively with risk technology and reporting groups, develop an in-depth understanding of available data sources and appropriately leverage internal systems, databases to build efficient, scalable platform to analyze and report on investment risk
  • Work with management and partner investment management firms to collect data requirements, and design data processes while maintain data governance standards
  • Work with first line technology teams to define data sources, develop data dictionaries, define relations, dependencies, and business logic for the platform
  • Work with risk technology teams to develop data pipelines, maintain data quality and timeliness.
  • Continually document architecture and procedures
  • 8 plus years total work experience preferred. Experience in quantitative finance and technology preferred.
  • Bachelor's degree or the equivalent combination of education and experience.
  • Advanced degree in quantitative analysis preferred.
  • Has an in-depth understanding of data management, database design, and knowledge of liquidity, market risk and performance metrics
  • Experience with multiple asset classes and different investment vehicles a plus
  • Knowledge of techniques in data analysis, data mining and visualization, including time series, data cleaning/filtering, outlier management
  • Programming languages (Python, R, etc) and knowledge of reporting/visualization tools such as Tableau a plus
  • Experience in modern data management, such as Vertica/Hadoop and application of machine learning a plus
  • Must be able to work independently and flexibly and to iterate development with incomplete data.
  • Must be able to communicate project objectives, work cooperatively and to seek out expertise across the organization to enable delivery of projects
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