The newly formed Product Data Infrastructure & Analytics (PDIA) unit is a cross-functional team of SME professionals and technologists that supports front-, middle-, and back-office processes. The team operates through a centralized hub of data-driven capabilities, established to support the firm’s AUM growth by showcasing its portfolio strategies and asset management expertise. The team actively collaborates with Portfolio Management, Investment Strategists, Risk Management, and Client Services personnel across the U.S. Retail, Institutional, and International channels in critical activities such as New Product Launches and RFPs.
The core mission for the department is publishing best-quality risk and return attributes for the firm’s Mutual Funds, SMA and Institutional portfolios. This is achieved by ensuring that reliable data sourcing and computational methodologies are in place. The team certifies that product data and marketing exhibits maintain consistency with relevant benchmarks or client requested methodologies. Additionally, PDIA performs return attribution analysis and market data research to assist Portfolio Management and Investment Strategists in identifying trends and anomalies within portfolios or greater market environments.
The Associate role provides critical portfolio data integration support and analysis to the various arms of the organization. This professional will be have some experience and begin to specialize in areas of data capture, risk analytics, portfolio construction, investment management techniques, performance attribution, and market data research. This individual has a foundation in or will develop an understanding of the asset management industry and the various types of investment vehicles and the analytics required to create and maintain for marketing, sales and relationship management. The role is expected to perform the analytical processes including data mining, data modeling, and, ultimately, solving critical business problems by utilizing all applicable quantitative knowledge and statistical techniques.