We are seeking a Quantitative Analyst for a new position within our ESG research team. The successful applicant will possess a strong track-record in economic and statistical modelling with a passion for sustainability investing. The individual will be expected to thrive in an entrepreneurial environment and demonstrate ambition, teamwork skills and the ability to manage multiple projects and responsibilities.
What You’ll Do:
The job will consist of conducting quantitative equity analysis associated with the firm’s ESG engagement efforts. Responsibilities include (but are not limited to) the following:
- Conduct ESG research and quantitative analysis to develop the firm’s stewardship processes, data analytics, and impact reporting.
- Support the publication of data-driven thematic research (including an annual climate and sustainability report).
- Contribute to the development of the firm’s proprietary tools for use in monitoring ESG exposures including the development of environmental and social impact metrics and climate risk reporting.
- In collaboration with other portfolio managers, report on the performance and positioning to internal and external audiences using the firm’s proprietary oversight and management tools.
- Write concise, clear answers to client and prospect questions, based on knowledge of our portfolios and processes.
- Remain up-to-date on academic and industry ESG trends and developments.
- Support the Director of Responsible Investing and members of the ESG team in aspects of research, oversight, and preparation of external communications, presentations and materials.
We’re Looking for Teammates With:
- Strong academic record with an advanced degree in a quantitative field such as statistics, econometrics, computer science, or a similar discipline is required.
- 3 years of experience in a similar quantitative analyst role (e.g., asset manager, investment bank), exposure to ESG investing applied within a quantitative environment helpful.
- First-class quantitative research skills with experience parsing, processing, and analyzing large unstructured datasets (ideally text) and methods for working with large data and tools for data analysis (SQL, git, JIRA).
- Proven experience and fluency with data analysis techniques in Python, along with relevant statistics libraries (statsmodels, scikit-learn, scipy, numpy, pandas, matplotlib).
- Self-motivated, entrepreneurial individual with the ambition to succeed in and work collaboratively in an environment that demands multi-tasking and liaison across regional offices and time-zones.
- Well-organized, detail-oriented, and methodical approach to work, with an ability to organize and prioritize heavy workloads.
- Ability to work with others and resourcefulness in navigating an organization.
- Strong interpersonal and communications skills, with the ability to build and maintain relationships.