State Street - Quant Role - Fixed Income - Coding - Python

"Quant role", "Fixed Income", "Coding", "Phyton"

Job Description:

State Street Global Advisors (SSGA) is the asset management business of State Street Corporation, one of the world's leading providers of financial services to institutional investors with over $4 trillion in assets under management and a heritage dating back over two centuries. Backed by the strength and stability of the State Street organization, SSGA makes continual investments in asset management and client servicing platforms, resulting in a client-focused, solutions-driven orientation.

Position: SSGA is seeking an intermediate-level Quantitative Analyst for its Fixed Income Research team. The analyst will be a part of the team responsible for developing investment strategies, creating proprietary tools and solutions to improve investment decision-making process, engaging with various teams for thematic research and writing papers for publication. While the analyst will work in a collaborative environment, s/he is expected to make individual contributions and potentially lead a portion of research independently. As the team focus on delivering implementable solutions, the position may benefit from a level of market knowledge and attention to details. The ideal candidate has a minimum of 3 years of investment experience and demonstrated quantitative skills.

Requirements:

- A Bachelor's degree is required; advanced degree (MBA, MA, or MS) or CFA is preferred

- At least 3 years of investment experience (either in research or portfolio management) is required, preferably with the focus on one of the following areas: active security-selection, smart beta/risk premia research (including ESG as factors), portfolio construction and optimization. Research experience can be in either an academic or industry setting.

- Strong quantitative and programming skills are required. Knowledge of statistical packages (preferably R or Python) and intermediate level SQL is required. Experience dealing with large data sets is preferred.

- Familiarity with front-office tools such as FactSet, Bloomberg, etc. is highly recommended.

- Good communications skills and strong process, organizational, time and project management skills are necessary.

- A desire to develop creative and innovative solutions is highly recommended