We are one of the largest investment management organizations in the world, with over 1000 people working together to create long-term value.
Public Equity (EQ)
The Public Equity (EQ) department pursues active management strategies in equity investing. We invest globally and are organized along product groups specializing in different total return, relative return and quantitative strategies.
We are looking for a dynamic, self-motivated and experienced individual to join the Data Strategies team in Fundamental Equities, which works in close collaboration with all active strategy teams as well as the technology team. Responsibilities
- Build insights into portfolio drivers and performance through the application of analytics and data visualization techniques, as well as translate ideas and discussions into a process/product to aid portfolio and investment decision-making.
- Monitor and enhance existing reports which assess the exposure and performance of active strategies, and communicate these insights to the relevant teams.
- Participate in team portfolio discussions on investment ideas, portfolio decisions and execution - guide in bridging the technical and investment spaces.
- Coordinate cross-functional efforts with the Business Management Office and Equities Technology Team to develop as well as proliferate new tools and technology competencies within the department.
- Source and evaluate new datasets as part of our data mosaic, as well as build new capabilities for investment idea generation.
- Work with a variety of datasets derived from fundamental, market and alternative sources, to construct company and competition/industry level insights.
- A Bachelor's or Master's degree in Engineering/Applied Mathematics/Computer Science subjects with exposure to financial markets.
- Relevant experience in portfolio management or portfolio risk and performance analysis - and understand how alpha is generated along the investment process.
- Strong understanding of a typical investment process - idea generation/screening, portfolio construction, risk management - encompassing optimization theory, quantitative techniques, and general statistics.
- Proficient in working with a variety of datasets and aggregating/combining them.
- Logical and practical - strong interest in solving complex problems, and deconstructing them into principles.
- Existing or active progress toward CFA, CAIA or FRM qualifications a plus.
- Experience in data retrieval, analytics and visualization for financial data.
- Proficient with SQL, R and Python programming, as well as data visualization tools e.g. Tableau.
- Familiarity with financial platforms (e.g. Factset) and access to databases (e.g. Refinitiv) will be a plus.
- Passion for financial markets coupled with the ability to code.
- Ability to work effectively in a highly collaborative, team-oriented environment.
- Effective written and verbal communications skills, particularly in explaining technical concepts to a broad audience.