The Attribution team
The Attribution team is responsible for managing, facilitating, and reporting on the results of the attribution process at Arrowstreet Capital. This includes responsibility over the production of attribution, analyzing the results to ensure quality, and dissemination to stakeholders, including the portfolio management, research, business development, and client relationship management teams.
This individual will lead the Attribution team and will report to the head of Client Operations. The Attribution manager will play an important role working with the CIO and members of the research and portfolio management teams (the “investment team”) on strategic initiatives to enhance the attribution process. Individuals on the Attribution team must have a sound understanding of the portfolio construction and investment process, usage of derivatives, impact of leverage, how different aspects of the investment process may impact attribution results, and how to select the appropriate benchmark(s) to compute and report out attribution.
- Oversee the attribution process: Manage production of attribution, including interpreting calculations, reviewing results, and completing necessary checks to ensure high quality reporting. Own additional attribution related deliverables, including FactSet, portfolio commentary, and custom reporting.
- Responsibility over analytics and related analysis: Responsible for understanding the investment process, models, portfolio construction, and how such areas impact and influence the portfolio results. Individuals must be able to understand what necessary analytics should be developed and performed in order to understand, interpret, calculate, and explain the factors / drivers of portfolio results. Knowledge of statistics and regression analysis is critical. Proficiency in working with data, and knowledge of data programming languages such as Python, SQL, and R is preferred.
- Implement new initiatives: Work with the investment team to address various aspects of the portfolio construction process and the resulting impact on portfolio positions. Discuss ways to appropriately measure, model, and report attribution. Facilitate initiatives by working with the investment team during strategy sessions, documenting planned actions, working through analyses, leading initiatives with developers / IT team to implement agreed solutions, and presenting results to the investment team
- Design workflows and streamline processes: Develop, implement, and oversee procedures. Enhance and automate workflows to improve the attribution function. Design effective hand-offs across teams to collectively improve our process.
The ideal candidate will
- Have direct work experience in attribution analysis or portfolio analytics
- Have the ability to demonstrate understanding of security and portfolio characteristics, portfolio accounting, and valuation
- Have knowledge of attribution related software or programs such as Factset, MSCI Barra, or other pertinent systems
- Demonstrate excellent organizational, leadership, relationship management, time management, and verbal / written communication skills
- Possess problem solving skills with demonstrated ability to productively collaborate across teams
- Thrive in a fast-paced environment, and have the ability to work dynamically and manage multiple tasks/projects at one time while seeing each through to completion
- Work productively, both independently and in a team environment
- Demonstrate the ability to work on assignments and projects with minimal supervision while proactively providing updates, facilitating reviews of progress, and delivering to deadlines
- Bachelor’s degree is a requirement; Mathematics, Statistics, or Finance concentration is preferred
- A CFA, CIPM, or CAIA designation is preferred and direct experience in the financial service industry or asset management industry is required
- Approximately 8-12 years of relevant experience
- Possess strong data management and programming skills. Candidate will ideally have proficiency working with Python, SQL, R, and advanced Microsoft Excel
- Proficiency with large volumes of data, including data quality reviews, is required
- Analytical and structured thinking, with a keen interest in how things work
- Outstanding attention to detail
- Ability to proactively investigate issues and follow through to resolution