Manager, Quantitative Data Analytics and Insights

Job Description:

Position Description:

Performs software development to expand and improve technical and data infrastructure, research platforms, diagnostic tools, and reporting capabilities associated with multi-factor model risk forecasting, quantitative alpha models, big data analytics, and performance attribution. Participates in the continued development and incorporation of non-traditional and unstructured data, as well as data science applications to enhance the research and investment process. Runs capabilities at scale using Quant Platform capabilities (back-testing), computing core statistical measures, and Cloud Technologies. 

Primary Responsibilities:

• Coordinates production data management, model integrity, and end-to-end technical support for portfolio management, risk models, and quant research platforms.

• Provides analytic solutions and reporting frameworks to partners and senior leaders across the organization. 

• Delivers innovative data visualization and analytic tools capable of illustrating point-in-time and time series investment themes, portfolio exposures, and factors driving fund performance.

• Provides oversight, maintenance, quality assurance, and operational support of analytic and reporting environments to ensure timely and accurate investment intelligence is delivered for direct use within the portfolio management process.

• Oversees daily, weekly, and monthly production reporting cycles across the analytic environments.

• Ensures all required input data is available, processes run successfully, statistical output is accurate, and reports are generated properly.

• Responds to ad-hoc data analysis requests in support of projects performed by equity, fixed income or multi-asset class Quant Analysts.

• Develops new processes, performs calculations, identifies anomalies, and produces new reporting capabilities.

• Contributes to complex projects within a fast-paced environment.

• Liaises with investment professionals to gather requirements and achieve deliverables of technical development teams.

Education and Experience:

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Mathematics, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Manager, Quantitative Data Analytics and Insights (or closely related occupation) performing quantitative investment research in a fixed income investment domain. 

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, Financial Mathematics, or a closely related field (or foreign education equivalent) and one (1) year of experience as a Manager, Quantitative Data Analytics and Insights (or closely related occupation) performing quantitative investment research in a fixed income investment domain.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) performing advanced data analysis for security-level analytics and fixed income products, using Bloomberg data (price, yield, Option-Adjusted Spread (OAS), Option-Adjusted Duration (OAD), and valuation); and performing  data validation and model enhancements, and providing advisory services for fixed income market data operations, using python packages (Pandas, SciPy, and Matplotlib).  

• DE performing stress test simulation for money market funds (asset backed secured and unsecured bonds) in accordance with Rule 2a-7, using Python (XLWings or OpenPyXL) for data interaction and Excel VBA to generate NAV results under various redemption and liquidity scenarios. 

• DE developing performance attribution factor analysis tools for Fixed Income Funds, using R-Shiny, Python-Flask, or Django (as the back-end) and Dash-Plotly, Angular, or Reach (as the front-end); developing Application Programming Interfaces (APIs) for seamless analytics data retrieval from platforms (Bloomberg); and creating interactive web dashboards to present asset performance insights, using R-Shiny, Python-Flask, or Django. 

• DE developing index rebalancing and validation (daily and monthly) processes according to methodology rules; developing factor risk models for funds to analyze risk and inform sector allocation, using Statsmodels python package and SciKit-learn; and generating client-facing reports and incorporating what-if scenario analysis (to support investment strategies).

Salary:  $131,082.00 to $141,000.00/year.

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