Asset Management - GFICC - Quantitative Researcher with ESG data modelling experience - Vice President
Location: Greater London
Job Type: Full time
The GFICC Quantitative Solution (QS) team is responsible for quantitative research to complement the strong fundamental analysis framework within the fixed income business at JP Morgan Asset Management. The team is also responsible for building out and managing customizable, systematic fixed income solutions to meet the needs of JP Morgan Asset management clients.
We are looking for a London-based quantitative researcher to join the team at VP level. Key responsibilities include quantitative research spanning both quantitative signal generation and portfolio implementation to drive fixed income portfolio outcomes. Part of the focus will be on the research and implementation of ESG strategies and data metrics in fixed income. The candidate will also be expected to contribute to the performance of the QS strategies as well as collaborate with the broader active portfolio management teams within GFICC.
- Research efficient portfolio construction methodologies and enhance the team’s existing systematic fixed income strategies;
- Research, develop and assess sustainable investment approaches in FI to be used in both active and quantitative strategies;
- Assess and enhance ESG analytics and metrics for measuring and improving the management of ESG within GFICC portfolios;
- Be involved in the full research process: idea generation, data collection, modeling, and articulation of strategies to key stakeholders across bottom-up credit and asset allocation;
- Collaborate in a team environment with researchers, portfolio managers and contribute to custom built IT platform;
- The position would involve extensive programming and database related work;
- Partnering with other researchers and portfolio management teams in developing solutions for concrete portfolio management problems;
- Developing and maintaining strong relationships with cutting edge researchers in both the professional and academic communities to fuel their research;
- Collaborating with all internal quantitative analysts to drive information sharing and leverage expertise.
QS Team members typically have track records of outstanding professional and academic achievement. Candidates should have:
- An advanced hard science degree, with a strong interest in the capital markets;
- Proficiency in Python, SQL and Bloomberg, as well as other 3rd party providers of large datasets;
- Experience of working with large datasets via databases and data feeds;
- Experience specifically in developing quantitative drivers for fixed income portfolios and implementing techniques for efficient fixed income portfolio construction;
- Knowledge and experience of implementing ESG data within a fixed income context;
- A strong emphasis on teamwork whilst also being self-motivated and excelling at conducting independent research;
- Sound verbal communication skills, being able to discuss projects simply and concisely with both experts and non-experts alike and being capable of interacting closely with our Quant IT support teams.