Principal Data Scientist, Quant Data Strategy

Job Description:

The Principal Data Scientist (Quant Services) position is responsible for providing guidance and performing business, systems & data analysis around Quant services. This will include overseeing daily/weekly/monthly production cycles across Quant, responding to ad-hoc data analysis requests in support of projects performed by Quant Research Analysts and leading the resolution of any escalated requests/issues through close coordination with members from Quant Dev, Quant Research, Data Strategy, Global Data Services and Portfolio Engineering teams to insure timely remediation. The Senior Manager Data Strategy Data Strategy will play an important role in the coordination of all data-related tasks, business planning and prioritization within the SAI Quant domain. 

The Team

SAI Data Strategy team is responsible for building a center of data excellence within SAI to establish and implement best practices around Data Management, Quality, Distribution and Innovation.   Key functions of the team include data sourcing, ensuring good investment data quality and enabling effective data distribution & reporting within SAI and to its external partners. The team also leads business & data analysis, project management, data support for new product launches, regulatory & compliance data need fulfillment, marketing & communications material creation and advisor engagement like PI.

The Expertise You Have

• 6+ years hands on work experience
• Bachelor’s degree required, Master’s degree preferred
• Broad-based investment industry experience and proven analytical skills; experience with operations, business analysis, project management, and scorecard and metrics reporting
• Experience in Asset Management or with Managed Accounts is a plus
• Proficient with Microsoft Office suite; ability to produce executive-level PowerPoint presentations and manipulate data using Excel

The Skills You Bring

• Strong SQL, knowledge and ability to compose complicated ad hoc queries
• R, Python & Data Visualization or equivalent analytics tool experience a plus
• Highly analytical with the ability to quickly comprehend large data sets in order to develop new processes, perform calculations, identify anomalies, and/or produce new reporting capabilities.
• Familiarity with quantitative analytics, including fund and index performance measurement, predictive risk modeling, alpha research, stock selection models, and performance attribution.
• Strong hands-on project leadership skills with the drive to complete complex projects as a part of small teams within an extremely fast paced environment.  Capability to liaise with investment professionals to gather requirements and manage deliverables of technical development teams.
• Knowledge of securities, corporate actions, financial statement analysis, street estimates, pricing and performance data.
• Perform various statistical analyses (e.g., portfolio risk analytics) and coding tasks (e.g., pattern recognition or machine learning)
• Highly proactive and self-motivated with the ability to meet objectives under minimal supervision.

The Value You Deliver

• Perform business, systems, data analysis and participate in process design and acceptance testing across projects that require Quant research content and investment analytics.
• Oversee daily/weekly/monthly production cycles across Quant.  Ensure all required input data is available, processes run successfully, output is acceptable, and reports are generated properly. 
• Respond to ad-hoc data analysis requests in support of projects performed by Quant Research Analysts and other Investment professionals within Strategic Advisers.
• Lead the resolution of any escalated requests/issues through close coordination with members from Quant Dev, Quant Research, Data Strategy, Global Data Services and Portfolio Engineering teams to insure timely remediation
• Utilize deep understanding across all aspects of the Quant ecosystem including model construction,  inputs, outputs, definitions, calculations and any other meaningful information used within Quant / Portfolio Management environments

Category:

Data Analytics and Insights